Multi-sensor classification of tennis strokes

In this work, we investigate tennis stroke recognition using a single inertial measuring unit attached to a player’s forearm during a competitive match. This paper evaluates the best approach for stroke detection using either accelerometers, gyroscopes or magnetometers, which are embedded into the inertial measuring unit. This work concludes what is the optimal training data set for stroke classification and proves that classifiers can perform well when tested on players who were not used to train the classifier. This work provides a significant step forward for our overall goal, which is to develop next generation sports coaching tools using both inertial and visual sensors in an instrumented indoor sporting environment.

Lifetime cost of stroke subtypes in Australia: findings from the North East Melbourne stroke incidence study (NEMESIS)

Background and Purpose-: Little is known about any variations in resource use and costs of care between stroke subtypes, especially nonhospital costs. The purpose of this study was to describe the patterns of resource use and to estimate the first-year and lifetime costs for stroke subtypes.

Methods-: A cost-of-illness model was used to estimate the total first-year costs and lifetime costs of stroke subtypes for all strokes (subarachnoid hemorrhages excluded) that occurred in Australia during 1997. For each subtype, average cost per case during the first year and the present value of average cost per case over a lifetime were calculated. Resource use data obtained in the North East Melbourne Stroke Incidence Study (NEMESIS) were used.

Results-: The present value of total lifetime costs for all strokes was Aus $1.3 billion (US $985 million). Total lifetime costs were greatest for ischemic stroke (72%; Aus $936.8 million; US $709.7 million), followed by intracerebral hemorrhage (26%; Aus $334.5 million; US $253.4 million) and unclassified stroke (2%; Aus $30 million; US $22.7 million). The average cost per case during the first year was greatest for total anterior circulation infarction (Aus $28 266). Over a lifetime, the present value of average costs was greatest for intracerebral hemorrhage (Aus $73 542), followed by total anterior circulation infarction (Aus $53 020), partial anterior circulation infarction (Aus $50 692), posterior circulation infarction (Aus $37 270), lacunar infarction (Aus $34 470), and unclassified stroke (Aus $12 031).

Conclusions-: First-year and lifetime costs vary considerably between stroke subtypes. Variation in average length of total hospital stay is the main explanation for differences in first-year costs.

Derivation and Validation of a Novel Prognostic Scale (Modified–Stroke Subtype, Oxfordshire Community Stroke Project Classification, Age, and Prestroke Modified Rankin) to Predict Early Mortality in Acute Stroke

© 2015 American Heart Association, Inc.

Stroke severity, early recovery and outcome are each related with clinical classification of stroke: data from the 'Tinzaparin in Acute Ischaemic Stroke Trial (TAIST)

Introduction: Baseline severity and clinical stroke syndrome (Oxford Community Stroke Project, OCSP) classification are predictors of outcome in stroke. We used data from the ‘Tinzaparin in Acute Ischaemic Stroke Trial’ (TAIST) to assess the relationship between stroke severity, early recovery, outcome and OCSP syndrome. Methods: TAIST was a randomised controlled trial assessing the safety and efficacy of tinzaparin versus aspirin in 1,484 patients with acute ischaemic stroke. Severity was measured as the Scandinavian Neurological Stroke Scale (SNSS) at baseline and days 4, 7 and 10, and baseline OCSP clinical classification recorded: total anterior circulation infarct (TACI), partial anterior circulation infarct (PACI), lacunar infarct (LACI) and posterior circulation infarction (POCI). Recovery was calculated as change in SNSS from baseline at day 4 and 10. The relationship between stroke syndrome and SNSS at days 4 and 10, and outcome (modified Rankin scale at 90 days) were assessed. Results: Stroke severity was significantly different between TACI (most severe) and LACI (mildest) at all four time points (p<0.001), with no difference between PACI and POCI. The largest change in SNSS score occurred between baseline and day 4; improvement was least in TACI (median 2 units), compared to other groups (median 3 units) (p<0.001). If SNSS did not improve by day 4, then early recovery and late functional outcome tended to be limited irrespective of clinical syndrome (SNSS, baseline: 31, day 10: 32; mRS, day 90: 4); patients who recovered early tended to continue to improve and had better functional outcome irrespective of syndrome (SNSS, baseline: 35, day 10: 50; mRS, day 90: 2). Conclusions: Although functional outcome is related to baseline clinical syndrome (best with LACI, worst with TACI), patients who improve early have a more favourable functional outcome, irrespective of their OCSP syndrome. Hence, patients with a TACI syndrome may still achieve a reasonable outcome if early recovery occurs.

Neural network classification of cerebral embolic signals

The presence of circulating cerebral emboli represents an increased risk of stroke. The detection of such emboli is possible with the use of a transcranial Doppler ultrasound (TCD) system.

Lupus anticoagulant: a marker for stroke and venous thrombosis in primary Sjogren's syndrome

Antiphospholipid antibodies (aPL) and antiphospholipid syndrome (APS) have been described in primary Sjogren's syndrome (pSS) with controversial findings regarding aPL prevalence and their association with thrombotic events. We evaluated 100 consecutive pSS patients (American-European criteria) and 89 age-gender-ethnicity-matched healthy controls for IgG/IgM anticardiolipin (aCL), IgG/IgM anti-beta2-glycoprotein-I (a beta 2GPI), and lupus anticoagulant (LA) (positivity according to APS Sydney's criteria). Clinical analysis followed standardized interview and physical examination assessing thrombotic and nonthrombotic APS manifestations and thrombosis risk factors. aPLs were detected in 16 % patients and 5.6 % controls (p = 0.035). LA was the most common aPL in patients (9 %), followed by a beta 2GPI (5 %) and aCL (4 %). Thrombotic events occurred in five patients [stroke in two, myocardial infarction in one and deep-vein thrombosis (DVT) in four], but in none of controls (p = 0.061). Mean age at time of stroke was 35 years. Three patients with thrombotic events (including the two with stroke) had APS (Sydney's criteria) and were positive exclusively for LA. Comparison of patients with (n = 16) and without (n = 84) aPL revealed similar mean age, female predominance, and ethnicity (p > =0.387). Frequencies of livedo reticularis (25 vs. 4.8 %, p = 0.021), stroke (12.5 vs. 0 %, p = 0.024), and DVT (18.8 vs. 1.2 %, p = 0.013) were significantly higher in APL + patients. Conversely, frequencies of hypertension, dyslipidemia, diabetes, obesity, smoking, sedentarism, and hormonal contraception were similar in patients with or without aPL (p a parts per thousand yenaEuro parts per thousand 0.253). Our study identified LA as an important marker for APS in pSS, particularly for stroke in young patients, warranting routine evaluation of these antibodies and rigorous intervention in modifiable risk factors.

Synthesis of Hand Exoskeletons for the Rehabilitation of Post-Stroke Patients

This dissertation presents the synthesis of a hand exoskeleton (HE) for the rehabilitation of post-stroke patients. Through the analysis of state-of-the-art, a topological classification was proposed. Based on the proposed classification principles, the rehabilitation HEs were systematically analyzed and classified. This classification is helpful to both understand the reason of proposing certain solutions for specific applications and provide some useful guidelines for the design of a new HE, that was actually the primary motivation of this study. Further to this classification, a novel rehabilitation HE was designed to support patients in cylindrical shape grasping tasks with the aim of recovering the basic functions of manipulation. The proposed device comprises five planar mechanisms, one per finger, globally actuated by two electric motors. Indeed, the thumb flexion/extension movement is controlled by one actuator whereas a second actuator is devoted to the control of the flexion/extension of the other four fingers. By focusing on the single finger mechanism, intended as the basic model of the targeted HE, the feasibility study of three different 1 DOF mechanisms are analyzed: a 6-link mechanism, that is connected to the human finger only at its tip, an 8-link and a 12-link mechanisms where phalanges and articulations are part of the kinematic chain. The advantages and drawbacks of each mechanism are deeply analyzed with respect to targeted requirements: the 12-link mechanism was selected as the most suitable solution. The dimensional synthesis based on the Burmester theory as well as kinematic and static analyses were separately done for all fingers in order to satisfy the desired specifications. The HE was finally designed and a prototype was built. The experimental results of the first tests are promising and demonstrate the potential for clinical applications of the proposed device in robot-assisted training of the human hand for grasping functions.

D-Dimers Predict Stroke Subtype when Assessed Early

Early classification of ischemic stroke subtype is important for secondary stroke prevention and may guide further investigations.

Neuroimaging in childhood arterial ischaemic stroke: evaluation of imaging modalities and aetiologies

Aim The aim of this study was to describe neuroimaging patterns associated with arterial ischaemic stroke (AIS) in childhood and to differentiate them according to stroke aetiology. Method Clinical and neuroimaging (acute and follow-up) findings were analysed prospectively in 79 children (48 males, 31 females) aged 2 months to 15 years 8 months (median 5y 3mo) at the time of stroke by the Swiss Neuropaediatric Stroke Registry from 2000 to 2006. Results Stroke was confirmed in the acute period in 36 out of 41 children who underwent computed tomography, in 53 of 57 who underwent T2-weighted magnetic resonance imaging (MRI) and in all 48 children who underwent diffusion-weighted MRI. AIS occurred in the anterior cerebral artery (ACA) in 63 participants and in all cases was associated with lesions of the middle cerebral artery (MCA). The lesion was cortical-subcortical in 30 out of 63 children, cortical in 25 out of 63, and subcortical in 8 of 63 children. Among participants with AIS in the posterior circulation territory, the stroke was cortical-subcortical in 8 out of 16, cortical in 5 of 16, and thalamic in 3 out of 16 children. Interpretation AIS mainly involves the anterior circulation territory, with both the ACA and the MCA being affected. The classification of Ganesan is an appropriate population-based classification for our Swiss cohort, but the neuroimaging pattern alone is insufficient to determine the aetiology of stroke in a paediatric population. The results show a poor correlation between lesion pattern and aetiology.

Apraxia in neurorehabilitation: Classification, assessment and treatment

Apraxia is a higher-order motor disorder impairing the ability to correctly perform skilled, purposive movements as the result of neurological disorders most commonly stroke, dementia and movement disorders. It is increasingly recognised that apraxia negatively influences activities of daily living (ADL). Early diagnosis and treatment should be part of the neurorehabilitation programme. The aim of the present article is to describe the most important subtypes of apraxia such as ideational and ideomotor apraxia as well as their impact on ADL and outcome. Furthermore, the relationship to associated disorders such as aphasia is discussed. Finally, strategies concerning assessment, management and treatment of the disorder are presented.

VOR gain by head impulse video-oculography differentiates acute vestibular neuritis from stroke

OBJECTIVE Vestibular neuritis is often mimicked by stroke (pseudoneuritis). Vestibular eye movements help discriminate the two conditions. We report vestibulo-ocular reflex (VOR) gain measures in neuritis and stroke presenting acute vestibular syndrome (AVS). METHODS Prospective cross-sectional study of AVS (acute continuous vertigo/dizziness lasting >24 h) at two academic centers. We measured horizontal head impulse test (HIT) VOR gains in 26 AVS patients using a video HIT device (ICS Impulse). All patients were assessed within 1 week of symptom onset. Diagnoses were confirmed by clinical examinations, brain magnetic resonance imaging with diffusion-weighted images, and follow-up. Brainstem and cerebellar strokes were classified by vascular territory-posterior inferior cerebellar artery (PICA) or anterior inferior cerebellar artery (AICA). RESULTS Diagnoses were vestibular neuritis (n = 16) and posterior fossa stroke (PICA, n = 7; AICA, n = 3). Mean HIT VOR gains (ipsilesional [standard error of the mean], contralesional [standard error of the mean]) were as follows: vestibular neuritis (0.52 [0.04], 0.87 [0.04]); PICA stroke (0.94 [0.04], 0.93 [0.04]); AICA stroke (0.84 [0.10], 0.74 [0.10]). VOR gains were asymmetric in neuritis (unilateral vestibulopathy) and symmetric in PICA stroke (bilaterally normal VOR), whereas gains in AICA stroke were heterogeneous (asymmetric, bilaterally low, or normal). In vestibular neuritis, borderline gains ranged from 0.62 to 0.73. Twenty patients (12 neuritis, six PICA strokes, two AICA strokes) had at least five interpretable HIT trials (for both ears), allowing an appropriate classification based on mean VOR gains per ear. Classifying AVS patients with bilateral VOR mean gains of 0.70 or more as suspected strokes yielded a total diagnostic accuracy of 90%, with stroke sensitivity of 88% and specificity of 92%. CONCLUSION Video HIT VOR gains differ between peripheral and central causes of AVS. PICA strokes were readily separated from neuritis using gain measures, but AICA strokes were at risk of being misclassified based on VOR gain alone.

Automated detection and classification of brain injury lesions on structural magnetic resonance imaging

El daño cerebral adquirido (DCA) es un problema social y sanitario grave, de magnitud creciente y de una gran complejidad diagnóstica y terapéutica. Su elevada incidencia, junto con el aumento de la supervivencia de los pacientes, una vez superada la fase aguda, lo convierten también en un problema de alta prevalencia. En concreto, según la Organización Mundial de la Salud (OMS) el DCA estará entre las 10 causas más comunes de discapacidad en el año 2020. La neurorrehabilitación permite mejorar el déficit tanto cognitivo como funcional y aumentar la autonomía de las personas con DCA. Con la incorporación de nuevas soluciones tecnológicas al proceso de neurorrehabilitación se pretende alcanzar un nuevo paradigma donde se puedan diseñar tratamientos que sean intensivos, personalizados, monitorizados y basados en la evidencia. Ya que son estas cuatro características las que aseguran que los tratamientos son eficaces. A diferencia de la mayor parte de las disciplinas médicas, no existen asociaciones de síntomas y signos de la alteración cognitiva que faciliten la orientación terapéutica. Actualmente, los tratamientos de neurorrehabilitación se diseñan en base a los resultados obtenidos en una batería de evaluación neuropsicológica que evalúa el nivel de afectación de cada una de las funciones cognitivas (memoria, atención, funciones ejecutivas, etc.). La línea de investigación en la que se enmarca este trabajo de investigación pretende diseñar y desarrollar un perfil cognitivo basado no sólo en el resultado obtenido en esa batería de test, sino también en información teórica que engloba tanto estructuras anatómicas como relaciones funcionales e información anatómica obtenida de los estudios de imagen. De esta forma, el perfil cognitivo utilizado para diseñar los tratamientos integra información personalizada y basada en la evidencia. Las técnicas de neuroimagen representan una herramienta fundamental en la identificación de lesiones para la generación de estos perfiles cognitivos. La aproximación clásica utilizada en la identificación de lesiones consiste en delinear manualmente regiones anatómicas cerebrales. Esta aproximación presenta diversos problemas relacionados con inconsistencias de criterio entre distintos clínicos, reproducibilidad y tiempo. Por tanto, la automatización de este procedimiento es fundamental para asegurar una extracción objetiva de información. La delineación automática de regiones anatómicas se realiza mediante el registro tanto contra atlas como contra otros estudios de imagen de distintos sujetos. Sin embargo, los cambios patológicos asociados al DCA están siempre asociados a anormalidades de intensidad y/o cambios en la localización de las estructuras. Este hecho provoca que los algoritmos de registro tradicionales basados en intensidad no funcionen correctamente y requieran la intervención del clínico para seleccionar ciertos puntos (que en esta tesis hemos denominado puntos singulares). Además estos algoritmos tampoco permiten que se produzcan deformaciones grandes deslocalizadas. Hecho que también puede ocurrir ante la presencia de lesiones provocadas por un accidente cerebrovascular (ACV) o un traumatismo craneoencefálico (TCE). Esta tesis se centra en el diseño, desarrollo e implementación de una metodología para la detección automática de estructuras lesionadas que integra algoritmos cuyo objetivo principal es generar resultados que puedan ser reproducibles y objetivos. Esta metodología se divide en cuatro etapas: pre-procesado, identificación de puntos singulares, registro y detección de lesiones. Los trabajos y resultados alcanzados en esta tesis son los siguientes: Pre-procesado. En esta primera etapa el objetivo es homogeneizar todos los datos de entrada con el objetivo de poder extraer conclusiones válidas de los resultados obtenidos. Esta etapa, por tanto, tiene un gran impacto en los resultados finales. Se compone de tres operaciones: eliminación del cráneo, normalización en intensidad y normalización espacial. Identificación de puntos singulares. El objetivo de esta etapa es automatizar la identificación de puntos anatómicos (puntos singulares). Esta etapa equivale a la identificación manual de puntos anatómicos por parte del clínico, permitiendo: identificar un mayor número de puntos lo que se traduce en mayor información; eliminar el factor asociado a la variabilidad inter-sujeto, por tanto, los resultados son reproducibles y objetivos; y elimina el tiempo invertido en el marcado manual de puntos. Este trabajo de investigación propone un algoritmo de identificación de puntos singulares (descriptor) basado en una solución multi-detector y que contiene información multi-paramétrica: espacial y asociada a la intensidad. Este algoritmo ha sido contrastado con otros algoritmos similares encontrados en el estado del arte. Registro. En esta etapa se pretenden poner en concordancia espacial dos estudios de imagen de sujetos/pacientes distintos. El algoritmo propuesto en este trabajo de investigación está basado en descriptores y su principal objetivo es el cálculo de un campo vectorial que permita introducir deformaciones deslocalizadas en la imagen (en distintas regiones de la imagen) y tan grandes como indique el vector de deformación asociado. El algoritmo propuesto ha sido comparado con otros algoritmos de registro utilizados en aplicaciones de neuroimagen que se utilizan con estudios de sujetos control. Los resultados obtenidos son prometedores y representan un nuevo contexto para la identificación automática de estructuras. Identificación de lesiones. En esta última etapa se identifican aquellas estructuras cuyas características asociadas a la localización espacial y al área o volumen han sido modificadas con respecto a una situación de normalidad. Para ello se realiza un estudio estadístico del atlas que se vaya a utilizar y se establecen los parámetros estadísticos de normalidad asociados a la localización y al área. En función de las estructuras delineadas en el atlas, se podrán identificar más o menos estructuras anatómicas, siendo nuestra metodología independiente del atlas seleccionado. En general, esta tesis doctoral corrobora las hipótesis de investigación postuladas relativas a la identificación automática de lesiones utilizando estudios de imagen médica estructural, concretamente estudios de resonancia magnética. Basándose en estos cimientos, se han abrir nuevos campos de investigación que contribuyan a la mejora en la detección de lesiones. ABSTRACT Brain injury constitutes a serious social and health problem of increasing magnitude and of great diagnostic and therapeutic complexity. Its high incidence and survival rate, after the initial critical phases, makes it a prevalent problem that needs to be addressed. In particular, according to the World Health Organization (WHO), brain injury will be among the 10 most common causes of disability by 2020. Neurorehabilitation improves both cognitive and functional deficits and increases the autonomy of brain injury patients. The incorporation of new technologies to the neurorehabilitation tries to reach a new paradigm focused on designing intensive, personalized, monitored and evidence-based treatments. Since these four characteristics ensure the effectivity of treatments. Contrary to most medical disciplines, it is not possible to link symptoms and cognitive disorder syndromes, to assist the therapist. Currently, neurorehabilitation treatments are planned considering the results obtained from a neuropsychological assessment battery, which evaluates the functional impairment of each cognitive function (memory, attention, executive functions, etc.). The research line, on which this PhD falls under, aims to design and develop a cognitive profile based not only on the results obtained in the assessment battery, but also on theoretical information that includes both anatomical structures and functional relationships and anatomical information obtained from medical imaging studies, such as magnetic resonance. Therefore, the cognitive profile used to design these treatments integrates information personalized and evidence-based. Neuroimaging techniques represent an essential tool to identify lesions and generate this type of cognitive dysfunctional profiles. Manual delineation of brain anatomical regions is the classical approach to identify brain anatomical regions. Manual approaches present several problems related to inconsistencies across different clinicians, time and repeatability. Automated delineation is done by registering brains to one another or to a template. However, when imaging studies contain lesions, there are several intensity abnormalities and location alterations that reduce the performance of most of the registration algorithms based on intensity parameters. Thus, specialists may have to manually interact with imaging studies to select landmarks (called singular points in this PhD) or identify regions of interest. These two solutions have the same inconvenient than manual approaches, mentioned before. Moreover, these registration algorithms do not allow large and distributed deformations. This type of deformations may also appear when a stroke or a traumatic brain injury (TBI) occur. This PhD is focused on the design, development and implementation of a new methodology to automatically identify lesions in anatomical structures. This methodology integrates algorithms whose main objective is to generate objective and reproducible results. It is divided into four stages: pre-processing, singular points identification, registration and lesion detection. Pre-processing stage. In this first stage, the aim is to standardize all input data in order to be able to draw valid conclusions from the results. Therefore, this stage has a direct impact on the final results. It consists of three steps: skull-stripping, spatial and intensity normalization. Singular points identification. This stage aims to automatize the identification of anatomical points (singular points). It involves the manual identification of anatomical points by the clinician. This automatic identification allows to identify a greater number of points which results in more information; to remove the factor associated to inter-subject variability and thus, the results are reproducible and objective; and to eliminate the time spent on manual marking. This PhD proposed an algorithm to automatically identify singular points (descriptor) based on a multi-detector approach. This algorithm contains multi-parametric (spatial and intensity) information. This algorithm has been compared with other similar algorithms found on the state of the art. Registration. The goal of this stage is to put in spatial correspondence two imaging studies of different subjects/patients. The algorithm proposed in this PhD is based on descriptors. Its main objective is to compute a vector field to introduce distributed deformations (changes in different imaging regions), as large as the deformation vector indicates. The proposed algorithm has been compared with other registration algorithms used on different neuroimaging applications which are used with control subjects. The obtained results are promising and they represent a new context for the automatic identification of anatomical structures. Lesion identification. This final stage aims to identify those anatomical structures whose characteristics associated to spatial location and area or volume has been modified with respect to a normal state. A statistical study of the atlas to be used is performed to establish which are the statistical parameters associated to the normal state. The anatomical structures that may be identified depend on the selected anatomical structures identified on the atlas. The proposed methodology is independent from the selected atlas. Overall, this PhD corroborates the investigated research hypotheses regarding the automatic identification of lesions based on structural medical imaging studies (resonance magnetic studies). Based on these foundations, new research fields to improve the automatic identification of lesions in brain injury can be proposed.