Indivíduos com limitações funcionais decorrentes do Acidente Vascular Cerebral (AVC) tem dificuldades em curto e longo prazo na percepção e controle postural. A proposta do trabalho é descrever o desenvolvimento de uma tecnologia assistiva (TA), que auxilia na percepção e controle postural, para pessoas com hemiparesia decorrente do AVC e profissionais de reabilitação. Utilizou-se na pesquisa a metodologia de produtos, as necessidades dos grupos converteram-se em requisitos da tecnologia, geração de modelos, otimizações e testes nas populações alvo foram realizados. A TA denominada: Smartvest, constitui-se de uma aplicação para smartphone e uma vestimenta que permite a calibração de posturas do tronco e envia sinais corretivos. A Smartvest foi desenvolvida em parceria com o Instituto de Ciências da Computação e Matemática Computacional da Universidade de São Paulo (ICMC/USP). A satisfação dos usuários foi analisada pelo instrumento Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0) de forma adaptada, a percepção da amplitude de movimentos (ADM) do tronco (flexão/extensão, rotação e flexão lateral) pela TA foi comparada a dispositivo de análise cinemática e conduziu-se um estudo da viabilidade terapêutica no processo de reabilitação. Os resultados obtidos demonstram que a tecnologia na análise cinemática pelo sistema Plug-in Gait da Vicon® representa a ADM do tronco com diferenças menores que 10º (graus). A Smartvest foi considerada um recurso viável para os objetivos da reabilitação e facilitação da atuação dos terapeutas (100%), atendeu princípios de conforto (65%), facilidade de uso (60%) e eficácia (45%) para pessoas com AVC, em atividades cotidianas da reabilitação observou-se que pessoas com AVC recebendo as orientações da TA alcançaram 3,13 vezes mais posturas corretas com menos erros de deslocamentos do tronco (1,75 vezes). A Smartvest apresentou potencial uso terapêutico na reabilitação como recurso de facilitação da percepção da postura. / Individuals with functional limitations due to Stroke have short- and long-term difficulties in perception and postural control. The purpose of this study is to describe the development of assistive technology (AT), which assists in postural perception and control, for people with hemiparesis and rehabilitation professionals. The methodology of products was used in the research, the needs of groups were transformed into technology requirements, model generation, optimizations and tests in the target populations were performed. The AT called: Smartvest, is a smartphone application and a dress that allows the calibration of postures of the trunk and sends corrective signals. Smartvest was developed in partnership with the Institute of Computer Science and Computational Mathematics of the University of São Paulo (ICMC / USP). The users\' satisfaction was analyzed by the Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0) in an adapted way, the perception of the trunk movement amplitude (flexion / extension, rotation and lateral flexion) by the AT was compared to a kinematic analysis device and a study of the therapeutic viability in the rehabilitation process was conducted. The results obtained demonstrate that the technology in kinematic analysis by the Vicon® Gait Plug-in system represents the trunk ADM with differences smaller than 10º (degrees). Smartvest was considered a viable resource for the rehabilitation and facilitation goals of therapists (100%), followed principles of comfort (65%), ease of use (60%) and effectiveness (45%) for people with stroke, in daily activities of rehabilitation, it was observed that people with stroke receiving the guidelines of AT achieved 3.13 times more correct postures with fewer trunk displacement errors (1.75 times). Smartvest presented potential therapeutic use in rehabilitation as a facilitator of perception of posture.

Wearable sensors can be used to monitor opioid use and other key behaviors of interest, and to prompt interventions that promote behavioral change. The effectiveness of such systems is threatened by the potential of a subject's deliberate non-compliance (DNC) to the monitoring. We define deliberate non-compliance as the process of giving one's device to someone else when surveillance is on-going. The principal aim of this thesis is to develop an approach to leverage movement and cardiac features from a wearable sensor to detect such deliberate non-compliance by individuals under surveillance for opioid use. Data from 11 participants who presented to the Emergency Department following an opioid overdose was analyzed. Using a personalized machine learning classifier (model), we evaluated if a snippet of blood volume pulse (BVP) and accelerometer data received is coming from the expected participant or an alternate person. Analysis of our classier shows the viability of this approach, as we were able to detect DNC (or compliance) with over 90% accuracy within 3 seconds of its occurrence.

Football safety has increased over time, in part due to improvements in equipment and body mechanics, but there are still inherent risks involved, including exposure to repetitive head impacts (RHI). Significant head impacts can result in a constellation of symptoms including nausea, vomiting, headache, dizziness, and amnesia, which typically assist in the diagnosis of concussion. However, it has been shown that subconcussive impacts may result in microstructural changes and physiological alterations in the brain. This is particularly concerning because athletes may be undergoing changes in the brain in the absence of outwardly visible symptoms. Poorer neurologic outcomes later in life have been associated with cumulative exposure rather than number of diagnosed concussions. Accelerometers installed in helmets have shown that college football players may receive up to 1,850 head impacts throughout the course of one season. The concussion rate is obviously much lower, indicating there are a high number of head impacts per diagnosed concussion. Axons are especially susceptible to damage from RHI because of their extension throughout the nervous system. The subtle changes thought to result from RHI are not easy to measure, but several modalities have been proposed. These include diffusion tensor imaging (DTI), plasma tau protein, and King-Devick testing. The proposed study will look to quantify cumulative head impact exposure in college football players prior to the start of a season and see if this has any impact on the variables. They will then participate in one season of football wearing helmet accelerometers to measure the number of head impacts sustained. Changes in the variables will be compared to non-contact sport college athletes. Data will be analyzed to determine if number of head impacts correlates with changes in variables and if prior head impact exposure has any effect on these changes. Data obtained from this study will have significant implications in the field of head injury. It may strengthen the use of several markers of brain injury that could be utilized in the future. Additionally, the effects of cumulative head impact exposure and one season of head impacts will be thoroughly examined. This information can be provided to trainers, coaches, and athletes to further improve football safety.

The research explores aspects of road surface measurement and monitoring, targeting some of the main challenges in the field, including cost and portability of high-speed inertial profilers. These challenges are due to the complexities of modern profilers to integrate various sensors while using advanced algorithms and processes to analyse measured sensor data. Novel techniques were proposed to improve the accuracy of road surface longitudinal profiles using inertial profilers. The thesis presents a Half-Wavelength Peak Matching (HWPM) model, designed for inertial profilers that integrate a laser displacement sensor and an accelerometer to evaluate surface irregularities. The model provides an alternative approach to drift correction in accelerometers, which is a major challenge when evaluating displacement from acceleration. The theory relies on using data from the laser displacement sensor to estimate a correction offset for the derived displacement. The study also proposes an alternative technique to evaluating vibration velocity, which improves on computational factors when compared to commonly used methods. The aim is to explore a different dimension to road roughness evaluation, by investigating the effect of surface irregularities on vehicle vibration. The measured samples show that the drift in the displacement calculated from the accelerometer increased as the vehicle speed at which the road measurement was taken increased. As such, the significance of the HWPM model is more apparent at higher vehicle speeds, where the results obtained show noticeable improvements to current techniques. All results and analysis carried out to validate the model are based on real-time data obtained from an inertial profiler that was designed and developed for the research. The profiler, which is designed for portability, scalability and accuracy, provides a Power Over Ethernet (POE) enabled solution to cope with the demand for high data transmission rates.

Purpose: Accelerometry is commonly used to objectively measure physical activity (PA), however, differential data collection methods and analysis techniques yield dissimilar outcomes. The aims of this research were to (1) understand how accelerometer output varies among accelerometers worn on the non-dominant wrist (NDW), dominant wrist (DW), and hip; (2) develop site-specific algorithms to predict activity type classification, activity intensity classification, and estimates of metabolic intensity; and (3) compare the algorithms in a free-living setting. Methods: Forty participants (16.8 – 64.2 yr) completed a sequence of sedentary and physical activities in a laboratory while wearing accelerometers on the NDW, DW, and hip. Participants also wore a portable metabolic analyzer to objectively measure oxygen consumption (VO2). One-second accelerometer output was compared across wear locations by activity type and intensity classifications (Aim 1). Accelerometer output data were transformed into variables related to the magnitude (ϒ), horizontal angle (φ), and inclination (θ) of acceleration, and used to develop algorithms for the NDW, DW, and hip. Random forest algorithms were developed to predict activity type classification (i.e., sedentary, lifestyle, and ambulatory) and activity intensity classification (i.e., sedentary, light, moderate, and vigorous), and regression models were built to predict VO2 (Aim 2). Following the laboratory visit, participants simultaneously wore an accelerometer at each of the three locations for three days of free-living data collection. The site-specific algorithms developed in Aim 2 were compared for equivalence (Aim 3). Aim 1 Results: Analysis of variance indicated that accelerometer output differed between the NDW, DW, and hip for all activities completed, except for lying supine. Differences were expected; thus, Pearson correlation coefficients were calculated between the NDW, DW, and hip, and compared across activity type and intensity classifications. For activity type, the relationships between all wear locations were different for all activity types (i.e., sedentary, lifestyle PA, and ambulatory PA). For activity intensity, the relationships between the wrists were significantly different between sedentary and light activities. Additionally, relationships between the NDW, DW, and hip differed between light and moderate, and light and vigorous PA for all wear locations. The disparate correlations indicated that accelerometer signals do not just increase in magnitude as intensity increases; rather they increase differentially by wear location and activity type. Aim 2 Results: Site-specific random forest algorithms were developed to predict activity type and intensity classification. The algorithms utilized 10-15 features of the accelerometer signal related to variability, location, and central tendency. The hip had prediction accuracies of 84.9% for activity type classification and 80.2% for activity intensity classification. The dominant wrist had activity type prediction accuracy of 83.6% and intensity prediction accuracy of 78.9%. The non-dominant wrist had prediction accuracies of 83.1% and 78.0% for activity type and intensity, respectively. The VO2 prediction algorithms had Mean Absolute Errors of 2.96 ml/kg/min for the hip, 3.34 ml/kg/min for the NDW, and 3.49 ml/kg/min for the DW. This equates to an average error of 0.93 metabolic equivalents (METs); algorithms currently used in practice yield errors of 0.89 to 2.00 METs. Aim 3 Results: The site-specific prediction algorithms were applied to free-living data. Using the random forest algorithms, activity type classification estimates differed by 2 to 82 minutes/day, and activity intensity classification estimates differed by 0 to 83 minutes/day; however, these differences were not significantly different. The VO2 prediction models provided estimates of PA within 0 to 57 minutes/day of one another. The hip provided the lowest estimates of MVPA, while the NDW provided the highest estimates, however the VO2 estimates from all wear locations were statistically equivalent to one another. Conclusion: The differential relationships among accelerometer outputs from the NDW, DW, and hip indicate that output differs based on activity type and intensity. This non-systematic error prevents scaling or comparing data collected at different wear locations and supports the need for site-specific analysis methods. Site-specific prediction algorithms provided comparable to improved performance over currently-utilized analysis methods in PA research, and the PA estimates were equivalent across wear locations. This research provides a more nuanced understanding of the impact of wear location on accelerometer output and alternative methods for analysis. Importantly, the algorithms created allow for comparisons to be made among data collected at the NDW, DW, and hip, which has not previously been possible.

Habilidades Motoras Fundamentais (HMFS) são movimentos básicos como correr e arremessar, cujo desenvolvimento ocorre na infância e deve ser mantida por toda vida. A proficiência nessas habilidades é desejável para a execução adequada das atividades diárias, recreativas e competitivas. A literatura relata uma associação entre as HMFS com um aumento do nível de atividade física (NAF), indicando que as pessoas mais habilidosas são mais confiantes para executar suas atividades e consequentemente, são mais ativas fisicamente. No entanto, não se conhece bem a relação e impacto das HMFS sobre o NAF. Quando se considera os benefícios conhecidos da atividade física (AF) e a natureza do desenvolvimento motor, é racional reconhecer que o professor de Educação Física (EF) é o principal responsável pelo desenvolvimento das HMFS com importante impacto no futuro estilo de vida dos seus alunos. Assim, o objetivo deste estudo foi descrever e investigar os níveis de HMFS e sua associação com NAF em escolares do ensino fundamental. Método: Participaram deste estudo 148 crianças saudáveis (70 meninos; 78 meninas) com idades entre seis e 10 anos. O teste TGMD-2 foi usado para classificar os níveis das HMFS (em sete escalas) nos subtestes (locomoção e controle de objetos) e no quociente do desenvolvimento motor grosso (QDMG). O NAF foi determinado por acelerometria (Actigraph wGT3X-BT) por meio de \"counts\", considerando o Vetor Magnitude (VM) Semanal de AF Moderada/Vigorosa (Total Semanal MV), para classificar o NAF Total Semanal MV como sedentário ou ativo, de acordo com as classificações de Chandler et al. (2015). A associação entre os escores padrões das HMFS com o QDMG e com o NAF foi verificada (Pearson). A influência das HMFS sobre o NAF Total Semanal MV foi estabelecida por regressão linear simples explicativa, considerando o NAF como variável dependente e os escores padronizados dos subtestes e o QDMG como variáveis independentes. Para todas as análises realizadas (SPSS 20.0) considerou-se ?=0,05. Resultados: Para o NAF Total Semanal MV foram identificadas baixas correlações estatisticamente significantes com QDMG (r=0,33: p<0,001), escore padrão da locomoção (r = 0,24; p=0,004) e escore padrão controle de objetos (r=0,32: p<0,001). A regressão linear (?) mostrou que o QDMG explica 33.3% da variância do NAF Total Semanal MV [FANOVA = 18,216, p=0.001; r2ajustado=0.105]. De modo semelhante, a variância do NAF Total Semanal MV é explicada em diferentes magnitudes pelo escore padrão da locomoção (?=23.8%; [FANOVA = 8.738, p=0.004; r2=0.050]) e pelo controle de objetos (?=32,3%; [FANOVA = 16,991, p=0.001; r2=0.098]). As HMFS apresentaram um impacto de 33% no NAF Total Semanal MV. Crianças com níveis mais altos de HMFS foram as mais ativas fisicamente. Conclusão: Assim, pode-se considerar que os níveis de proficiência das HMFS têm importante influência no NAF Total Semanal MV das crianças. Diante disso, as crianças das séries iniciais necessitam de planos de ensino enfatizando o desenvolvimento das HMFS, pois são prioritariamente desenvolvidas nessa fase da infância / Fundamental Motor Skills (FMS) are basic movements, such as running and throwing, whose development occurs in childhood and must be maintained throughout life. Proficiency in these skills is desirable for proper performance of daily, recreational and competitive activities. The literature reports an association between FMS with an increase in the level of physical activity (LPA), indicating that people who are more skilled are more confident to perform activities and consequently, are more physically active. However, it is not well understood the relationship and impact of FMS on LPA. When considering the known benefits of physical activity (PA) and the nature of motor development, it is rational to recognize that the Physical Education (PE) teacher is the most responsible for the development of FMS with important impact on the future lifestyle of his/her students. Thus, the objective of this study was to describe and investigate levels of FMS and their association with LPA in elementary school students. Method: A total of 148 healthy children (70 boys, 78 girls) with ages between six and 10 years participated in this study. The TGMD-2 test was used to classify FMS levels (on seven scales) in the subtests (locomotor and object control) and in the Gross Motor Quotient (GMQ). The LPA was determined by accelerometry (Actigraph wGT3X-BT) by means of \"counts\", considering the Magnitude Vector (MV) Weekly of Moderate/Vigorous PA (Total Weekly MV), to classify the LPA Total Weekly VM as sedentary or active, according to the classifications of Chandler et al. (2015). The association between FMS standard scores with GMQ and LPA was verified (Pearson). The influence of the FMS on the LPA Total Weekly MV was established by simple linear regression, considering the LPA as the dependent variable and the standardized scores of the subtests and the GMQ as independent variables. All analyzes were performed considering ? = 0.05. Results: For the LPA Total Weekly MV, low statistically significant correlations were identified with GMQ (r = 0.33: p <0.001), standard locomotor score (r = 0.24, p = 0.004) p <0.001) and standard object control score (r = 0.32: p <0.001). The linear regression (?) showed that the GMQ explains 33.3% of the variance of the LPA Total Weekly MV [FANOVA = 18,216, p = 0.001; r2 set = 0.105]. Similarly, the variance of the LPA Total Weekly MV is explained in different magnitudes by the standard locomotor score (? = 23.8%, [FANOVA = 8.738, p = 0.004, r2 = 0.050]) and object control (?=32, 3%; [FANOVA = 16,991, p=0.001; r2=0.098]). FMS had a 33% impact on LPA Total Weekly MV. Children with higher levels of FMS were the most physically active. Conclusion: Thus, it can be considered that FMS proficiency levels have an important influence on children\'s LPA Total Weekly MV. Faced with this, children in early grade need teaching plans emphasizing the development FMS, as they are primarily developed at this stage of childhood

The assessment of vertical jump performance is widely undertaken by coaches and sports scientists because of its strong relationship with sports performances including those in weightlifting, sprinting, and cycling. With the development of accelerometer based testing devices the traditional vertical jump field test may offer a more detailed evaluation of an athlete's performance capacity. However, little data are available on the reliability of this technology and the impact of sampling frequency on reliability. PURPOSE: To determine the reliability of accelerometer based performance measurements during countermovement vertical jumps and the influence of sampling frequency on reliability. METHODS: Ten college aged men (age = 23.6 ± 3.1 y; height = 180.1 ± 6.3 cm; mass = 85.0 ± 15.2kg; body fat = 14.2 ± 6.5%) performed two series of five restricted (no arm swing) zero load countermovement vertical jumps. During each jump a triaxial accelerometer that sampled at 500 Hz was used to assess acceleration, from which peak force (PF), rate of force development (RFD), peak power output (PP), peak velocity (PV), flight time (FT), and peak vertical displacement (VD) were derived and analyzed using a custom LabView Program. This program was used to re-sample the data collected at 500 Hz to 250Hz, 125 Hz and 50 Hz, which were then analyzed. The reliability of the accelerometer system was assessed with the use of intraclass correlations, while precision was determined with the use of the coefficient of variation (CV), and criterion validity was assessed via Pearsons correlation. RESULTS: At 500 Hz the accelerometer was reliable for PF (ICC = 0.94), RFD (ICC = 0.92), PP (ICC = 0.87), FT (ICC = 0.93), and VD (ICC = 0.93). Additionally, reliability was maintained at 250Hz for PF(0.95), RFD(0.92), PP(ICC = 0.86), FT(ICC = 0.93) and VD(ICC = 0.92). Good precision was determined for PF (CV = 7.3%), PV (CV = 7.6%), FT (CV = 2.3%), and VD(CV = 4.7%) at 500 Hz. Additionally precision was maintained at 250Hz for PF (CV = 6.8%), PV (CV = 7.7%), FT (CV = 2.4%), and VD(CV = 4.9%). Finally, criterion validity was high for PF(r = 0.96), RFD(r = 0.97), PP(r = 0.99), PV(r = 0.99), FT(r = 0.99) and VD(r = 0.99) when comparing the 250Hz data to the 500 Hz data. When sampling frequency was decreased below 250Hz reliability, precision and criterion validity all decreased. CONCLUSIONS: The accelerometer used in this investigation produced reliable, precise and valid for assessments of PF, PP, FT, and VD data at sampling frequencies ≥250Hz. PRACTICAL APPLICATIONS: For vertical jump applications it appears that accelerometers must have a minimum sampling frequency of 250Hz in order to maintain reliability, precision and validity. Therefore when assessing athlete performance, it is essential that the strength and conditioning professional consider sampling rate when utilizing this technology. ACKNOWLEDGMENTS: This investigation was partially supported by MyoTest Inc., which donated the accelerometer system used in this investigation.

Abstract available in the Journal of Strength and Conditioning Research.

The purposes of the study were to track weightlifters' barbell acceleration with a portable accelerometer over three training sessions to examine test–retest reliability and to compare peak barbell acceleration at different training intensities. Twelve nationally ranked weightlifters volunteered for this study. The portable accelerometer was attached to the right side of the barbell to measure barbell resultant acceleration during the snatch lift at a sampling frequency of 100 Hz. The data were collected over three training sessions at intensity levels of 80%, 85%, and 90% of one repetition maximum. The data were analyzed using intra-class correlation coefficients (ICCs) for the three training sessions and one-way repeated measure ANOVA to compare the difference in peak barbell acceleration at three intensities. Results showed that the device was highly reliable with an ICC of 0.88 and 95% confidence interval of 0.81–0.93. There were significant differences in peak barbell acceleration at various lifting intensities, indicating a decline of the acceleration as the mass of the barbell became heavier. The portable accelerometer seems useful in measuring barbell acceleration data, which can be analyzed in future studies to monitor a weightlifter's performance in a practical setting instead of testing at a laboratory.

Some seabirds (such as Northern Gannets and Brown Boobies) can dive from heights as high as 30 m reaching speeds of up to 24 m/s as they impact the water surface. It is perceived that physical geometry, particularly of the beak, allows them to endure relatively high impact forces that could otherwise kill non-diving birds. Acceleration data from simplified models of diving birds agree with simulated data for one species (Northern Gannet), however, no reliable experimental data with real bird geometries exist for comparison purposes. This study utilizes eleven 3D printed diving birds (five plunge-diving, five surface-diving and one dipper) with embedded accelerometers to measure water-entry impact accelerations for impact velocities ranging between 4.4 - 23.2 m/s. Impact forces for all bird types are found to be comparable under similar impact conditions and well within the safe zone characterized by neck strength as found in recent studies. However, the time each bird requires to reach maximum impact acceleration and its effect represented here by the derivative of acceleration (i.e., jerk), is different based on its beak and head shape. We show that surface diving birds cannot dive at high speeds as the non-dimensional jerk experienced exceeds a safe limit estimated from human impact analysis, whereas those by plunge divers do not.