An investigation into the spinal kinematics and lower limb impacts during cricket fast bowling and their association with lower back pain.

Cricket fast bowlers have been highlighted as having increased risk of injury when compared to the rest of the team. Lower back injury and more specifically, pain results in more time away from cricket than any other injury in the fast bowling population, with juniors displaying even greater risk compared with senior fast bowlers. Whilst lower back injury (confirmed musculoskeletal diagnoses, usually radiographically) in fast bowlers has been repeatedly investigated. Lower back pain (LBP), defined as pain resulting in time away from matchplay or training with or without a formal diagnosis, (highlighted to display a different relationship to injury) has received little attention in fast bowling literature. High bowling workloads (usually recorded in overs or days bowled) and the immature spine of junior fast bowlers have been highlighted as significantly increasing risk of injury. However, research regarding specific kinematic and kinetic risk factors requires further attention. Therefore, this study aimed to address current methodological limitations to investigate the association between spinal kinematics and lower limb impacts during fast bowling and risk of LBP in junior and senior fast bowlers. This study compares bowling kinematics and lower limb impacts in junior and senior fast bowlers and retrospective and prospective LBP risk, to provide additional insight into the clinical biomechanics of fast bowling. This study has shown inertial sensors and accelerometers are a valid (r>0.8 for 79% of variables, RMSEP = 0.3-1.5°) and reliable (ICC’s >0.8 and SEM<3.4g and 9°) method of analysing fast bowling lower limb impacts and spinal kinematics and may therefore be an acceptable alternative to current methodologies. Analysis of tibial impacts on different playing surfaces displayed larger impacts on outdoor artificial surfaces (26.6g) compared with grass (24.7g) and indoor rubber (22.0g) and wood (17.8g). Highlighting, large workloads on outdoor artificial surfaces may increase injury risk, with a wooden indoor surface more favourable. Retrospective and prospective LBP and injury data highlighted that senior fast bowlers with known spinal pathologies displayed four times greater risk of future LBP. However, this was not necessarily the case in junior bowlers. Results highlighted that peak accelerations at back-foot impact were higher in bowlers with no history of LBP, as well as bowlers that did not develop LBP in the follow-up season with differences between 8-10g seen in peak tibial acceleration. This may be a potential mechanism of reducing load at front-foot impact (which showed few notable differences between groups). Junior bowlers with a history of LBP displayed less contralateral thoracic rotation at back-foot impact and consequently a lower overall range. However, this trend was not displayed in senior bowlers. Senior bowlers, with either a history of LBP or that went on to develop LBP bowled with almost double lumbar extension (9° to 16°) resulting in a 12° increase in thoracolumbar extension at back-foot impact. Therefore, this study suggests that higher magnitudes of fast bowling impacts may not be synonymous with increased risk of LBP, however spinal kinematics at back-foot impact may provide some insight into bowlers’ risk of developing LBP. The effect of these recommendations on fast bowling performance was analysed through a correlation of impact and spinal kinematics with ball release speed. This highlighted that the recommendations to reduced risk of LBP are not likely to affect ball release speed, as only sacral loading rate at back foot impact and thoracic lateral flexion at FFI showed significant correlations with ball release speed (r=.521 and .629 respectively). Overall this study has demonstrated the application of novel technology applied to the live cricket fast bowling situation, overcoming limitations of previous methods. The method was valid, reliable and sensitive enough to determine significant differences in the spinal kinematics which were associated with LBP history or with developing LBP in the follow-up season and these were specific to junior and senior bowlers. These new insights will help to inform surveillance and coaching practices in the quest to reduce the injurious nature of fast bowling

Developing a method for quantifying hip joint angles and moments during walking using neural networks and wearables

Quantifying hip angles/moments during gait is critical for improving hip pathology diagnostic and treatment methods. Recent work has validated approaches combining wearables with artificial neural networks (ANNs) for cheaper, portable hip joint angle/moment computation. This study developed a Wearable-ANN approach for calculating hip joint angles/moments during walking in the sagittal/frontal planes with data from 17 healthy subjects, leveraging one shin-mounted inertial measurement unit (IMU) and a force-measuring insole for data capture. Compared to the benchmark approach, a two hidden layer ANN (n = 5 nodes per layer) achieved an average rRMSE = 15% and R2=0.85 across outputs, subjects and training rounds

Wearables for Movement Analysis in Healthcare

Quantitative movement analysis is widely used in clinical practice and research to investigate movement disorders objectively and in a complete way. Conventionally, body segment kinematic and kinetic parameters are measured in gait laboratories using marker-based optoelectronic systems, force plates, and electromyographic systems. Although movement analyses are considered accurate, the availability of specific laboratories, high costs, and dependency on trained users sometimes limit its use in clinical practice. A variety of compact wearable sensors are available today and have allowed researchers and clinicians to pursue applications in which individuals are monitored in their homes and in community settings within different fields of study, such movement analysis. Wearable sensors may thus contribute to the implementation of quantitative movement analyses even during out-patient use to reduce evaluation times and to provide objective, quantifiable data on the patients’ capabilities, unobtrusively and continuously, for clinical purposes

Towards understanding the functionality of foot orthosis based on foot structure and function

The raw data related to the second study of this thesis (Chapter 3) is available online in the section of supporting information at https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0232677. These files present the following data: S1 File. The pattern of foot orthosis depression/reformation for healthy subjects during walking with sport versus regular foot orthosis. S2 File. Raw data for the training session of sport foot orthosis. This Excel file consists three sheets in which the position of triad markers, the orientation of triad markers and the position of markers on plantar surface of foot orthosis are provided respectively. S3 File. Raw data for walking with sport foot orthosis. This Excel file consists two sheets in which the position of triad markers and the orientation of triad markers are provided respectively for subject 1. S4 File. The results of each participant during walking with sport foot orthosis. This .mat file includes “DispEachPoint” and “DispEachPointMean” which shows the displacement of each predicted marker on foot orthosis plantar surface during stance phase of walking relative to its corresponding position in static non weight-bearing for each trial and the average of trials respectively. In addition, “loc_stance” and “loc_meanstance” show the location of each predicted marker during stance phase of walking. “peaks” and “peaksMean” represent the minimum (depression) and maximum (reformation) value of displacement during walking S5 File. The results of each participant during walking with regular foot orthosis. This .mat file includes “DispEachPoint” and “DispEachPointMean” which shows the displacement of each predicted marker on foot orthosis plantar surface during stance phase of walking relative to its corresponding position in static non weight-bearing for each trial and the average of trials respectively. In addition, “loc_stance” and “loc_meanstance” show the location of each predicted marker during stance phase of walking. “peaks” and “peaksMean” represent the minimum (depression) and maximum (reformation) value of displacement during walkingLes orthèses plantaires (OP) sont des dispositifs médicaux fréquemment utilisés pour réduire les douleurs et blessures de surutilisation, notamment chez les personnes ayant les pieds plats. Le port d'OP permettrait de corriger les altérations biomécaniques attribuées à la déformation du pied plat, que sont la perte de l’arche longitudinale médiale et la pronation excessive du pied. Cependant, le manque de compréhension de la fonction des OP entraine une grande variabilité des OP prescrites en milieu clinique. L'objectif de cette thèse est d'approfondir les connaissances sur l’effet des OP sur la biomécanique, de quantifier les déformations des OP à la marche et de mettre en relation ces déformations avec la biomécanique du pied. La première étude a évalué la manière dont les différentes conceptions d'OP imposent des modifications dans le mouvement et le chargement appliqué sur le pied. Cet objectif a été atteint grâce à une revue systématique traitant des effets des OP sur la cinématique et la cinétique du membre inférieur pendant la marche chez des personnes ayant des pieds normaux. Les critères d'inclusion ont réduit les études à celles qui ont fait état des résultats pour les géométries les plus fréquentes des OP, à savoir les biseaux, les supports d’arche et les stabilisateurs de talon. La revue a mis en évidence que les orthèses avec un biseau médial peuvent réduire le moment d'éversion de la cheville. Aucune évidence significative n'a été trouvée dans notre méta-analyse sur l'efficacité des orthèses incluant des supports d’arche ou des stabilisateurs de talon. Les différents procédés et matériaux utilisés dans la conception des OP ainsi que les caractéristiques des pieds des participants pourraient expliquer la variabilité retrouvée au regard des effets des OP sur la biomécanique. La deuxième étude a apporté des informations précieuses et inédites sur le comportement dynamique des OP à la marche. La cinématique du contour des OP a été utilisée pour prédire la déformation de leur surface plantaire pendant la marche chez 13 individus ayant des pieds normaux en utilisant un réseau de neurones artificiels. Une erreur moyenne inférieure à 0,6 mm a été obtenue pour nos prédictions. En plus de la précision des prédictions, le modèle a été capable de différencier le patron de déformations pour deux OP de rigidités différentes et entre les participants inclus dans l’étude. Enfin, dans une troisième étude, nous avons identifié la relation entre la déformation des OP personnalisées et la biomécanique du pied à la marche chez 17 personnes avec des pieds plats. L'utilisation de modèles linéaires mixtes a permis d’exprimer les variations de la déformation des OP dans différentes régions en fonction des variables cinématiques du pied et de pressions plantaires. Cette étude a montré que l'interaction pied-OP varie selon les différentes régions de l’OP et les différentes phases du cycle de marche. Ainsi, des lignes directrices préliminaires ont été fournies afin de standardiser et optimiser la conception des OP. Dans l'ensemble, les résultats de cette thèse justifient l'importance d’'intégrer des caractéristiques dynamiques du pied de chaque individu dans la conception d'OP personnalisées. Des études futures pourraient étendre les modèles de prédiction de l'interaction pied-OP en incluant d'autres paramètres biomécaniques tels que les moments articulaires, les activations musculaires et la morphologie du pied. De tels modèles pourraient être utilisés pour développer des fonctions coût pour l'optimisation de la conception des OP par une approche itérative utilisant la simulation par les éléments finis.Foot orthoses (FOs) are frequently used medical devices to manage overuse injuries and pain in flatfoot individuals. Wearing FOs can result in improving the biomechanical alterations attributed to flatfoot deformity such as the loss of medial longitudinal arch and excessive foot pronation. However, a lack of a clear understanding of the function of FOs contributes to the highly variable FOs prescribed in clinical practice. The objective of this thesis was to deepen the knowledge about the biomechanical outcomes of FOs and to formulate the dynamic behaviour of FOs as a function of foot biomechanics during gait. The primary study investigated how different designs of FOs impose alterations in foot motion and loading. This objective was achieved through a systematic review of all literature reporting the kinematics and kinetics of the lower body during walking with FOs in healthy individuals. The inclusion criteria narrowed the studies to the ones which reported the outcomes for common designs of FOs, namely posting, arch support, and heel support. The review identified some evidence that FOs with medial posting can decrease ankle eversion moment. No significant evidence was found in our meta-analysis for the efficiency of arch supported and heel supported FOs. The findings of this study revealed that differences in FO design and material as well as foot characteristics of participants could explain the variations in biomechanical outcomes of FOs. The second study provided valuable information on the dynamic behaviour of customized FOs. The kinematics of FO contour was used to predict the deformation of FO plantar surface in 13 healthy individuals during walking using an artificial intelligence approach. An average error below 0.6 mm was achieved for our predictions. In addition to the prediction accuracy, the model was capable to differentiate between different rigidities of FOs and between included participants in terms of range and pattern of deformation. Finally, the third study identified the relationship between the deformation of customized FOs and foot biomechanics in 17 flatfoot individuals during walking. The use of linear mixed models made it possible to identify the variables of foot kinematics and region-dependent plantar pressure that could explain the variations in FO deformation. This study showed that the foot-FO interaction changes over different regions of FO and different phases of gait cycle. In addition, some preliminary guidelines were provided to standardize and optimize the design of FOs. Overall, the results of this thesis justify the importance of incorporating the dynamic characteristics of each individual’s foot into the design of customized FOs. Future studies can extend the predictive models for foot-FO interactions by including other determinants of foot biomechanics such as joint moments, muscle activation, and foot morphology. Based on such extended models, the cost functions could be devised for optimizing the designs of customized 3D printed FOs through an iterative approach using finite element modeling

Evaluation of mechanical load in the musculoskeletal system : development of experimental and modeling methodologies for the study of the effect of exercise in human models

Doutoramento em Motricidade Humana, na especialidade de BiomecânicaA major concern of Biomechanics research is the evaluation of the mechanical load and power that the human body develops and endorses when performing high to moderate sport activities. With the purpose of increasing performance and reducing the risk of injury, substantial advances were accomplished to pursuit this goal, either on the laboratory techniques as well as modelling and simulation. Traditionally, the main focus was the assessment of kinematics, kinetics and electromyography data to describe the main mechanics and neuromuscular behaviour, when performing a certain movement. The use of methodologies that enable the quantification of the effect of a particular joint moment of force in the entire body or the contribution of an individual muscle force to accelerate the centre of mass of the body is quite relevant in biomechanical analysis. This is particularly important when dealing with explosive movements such as those that occur in sports activities, or in the clinical field when dealing with abnormal movement. At the same time, the advances in imaging technology allows us the use of some of those techniques to gather subject-specific information, particularly the muscle architectural parameters that are crucial to the production of force, such as muscle volume, muscle physiological cross-section area and muscle pennation angle. In the course of this dissertation, we investigated the use and/or combination of different methodologies to study the effect of mechanical load in the lower limb musculoskeletal system during a cyclic stretch-shortening exercise. We aimed at using an integrated approach to better characterize the behaviour of the musculoskeletal system when subjected to this type of mechanical load.RESUMO: Uma das principais preocupações da investigação em Biomecânica é a avaliação da carga mecânica que o corpo desenvolve e que consegue suportar quando realiza ações desportivas com nível de desempenho de moderado a elevado. Com o objetivo de melhorar a performance mas reduzindo o risco de lesão, têm sido realizados avanços significativos quer nas técnicas laboratoriais e equipamentos, quer nas técnicas de modelação e simulação. A investigação tradicional em biomecânica tem o seu foco na avaliação da cinemática, cinética e função neuromuscular para descrever a mecânica do corpo e o comportamento neuromuscular, durante a execução de um determinado movimento. No entanto, a utilização de metodologias que permitam a quantificação do efeito de um determinado momento de força articular em todos os segmentos corporais ou a contribuição de um momento de força muscular individual na aceleração do centro de massa do corpo é bastante relevante na análise biomecânica. Isto é particularmente importante quando se lida com movimentos explosivos, tais como os que ocorrem em actividades desportivas, ou no âmbito clínico quando se tratam de condições não normais ou patológicas. Ao mesmo tempo, os avanços na tecnologia de imagem permitem a utilização de algumas destas técnicas para recolher informações específicas do sujeito, nomeadamente no que diz respeito aos parâmetros arquitectónicos do músculo, que são cruciais para a produção da força, tal como o volume muscular, a área de secção transversal fisiológica ou o ângulo de penação. No decurso deste trabalho, foi investigada a utilização e/ou combinação de diferentes metodologias para estudar o efeito da carga mecânica no sistema musculo-esquelético do membro inferior durante um exercício de alongamento-encurtamento realizado de forma cíclica. O principal objetivo foi utilizar uma abordagem integrada para melhor caracterizar o comportamento do sistema músculo-esquelético, quando submetido a este tipo de carga mecânica.FCT - Fundação para a Ciência e a Tecnologi

An investigation into the efficacy of kinematics and kinetics method for stride-characteristic measurements of horses trotting on a treadmill

The aim of this study was to investigate the validity of stride characteristic measurements taken from the sternum by means of an Optical Motion Capture System (OMCS) and an Inertia Measurement Unit (IMU), in comparison with OMCS hoof markers. Measurements were taken from sound horses of a range of breeds, trotting at self-selected speeds on a treadmill (OMCS N=15; IMU N=4). Hoof marker trajectories were compared in terms of dorsoventral position (pZ), craniocaudal velocity (vX) and dorsoventral velocity (vZ). Contra-laterally coupled limbs were compared at beginning and end of stance according to vX. A Girth Marker (GM) placed over the sternum was used to identify beginning and end of stance of each diagonal using dorsoventral acceleration (aZ) and dorsoventral velocity (vZ) respectively. These were compared with hoof marker vX. GM aZ and vZ were then validated against the same measurements taken by an IMU measuring at the same time from the same location. No significant difference (p < 0.05) was found by ANOVA between hoof marker trajectories pZ, vX or vZ at beginning or end of stance. No significant difference was found by t-test or ICC between contralaterally coupled limbs at beginning or end of stance. GM aZ and vZ could be used to identify beginning and end of stance for each diagonal without significant difference from hoof vX timings according to t-test and ICC. OMCS GM and IMU did not differ in terms of velocity (peak or trough timing or amplitude, or absolute difference: peak minus trough), or acceleration peak timing, trough timing or trough amplitude according to t-test or ICC. However, OMCS GM and IMU differed significantly in terms of acceleration peak amplitude (p = .01, ICC = 0.46) and absolute difference (p = .04, ICC = 0.66). The sternum can be used as a site to collect data providing accurate information on beginning or end of stance of horses with no advanced placement of contralaterally coupled limbs, whilst trotting at self selected speeds on a treadmill. Temporal acceleration data, and temporal or amplitudal velocity data are sufficient to identify beginning and end of stance from the sternum using an IMU. Amplitudal acceleration data from an IMU should be further investigated before assumed valid under these conditions

Wearable Sensors and Machine Learning based Human Movement Analysis – Applications in Sports and Medicine

Die Analyse menschlicher Bewegung außerhalb des Labors unter realen Bedingungen ist in den letzten Jahren sowohl in sportlichen als auch in medizinischen Anwendungen zunehmend bedeutender geworden. Mobile Sensoren, welche am Körper getragen werden, haben sich in diesem Zusammenhang als wertvolle Messinstrumente etabliert. Auf Grund des Umfangs, der Komplexität, der Heterogenität und der Störanfälligkeit der Daten werden vielseitige Analysemethoden eingesetzt, um die Daten zu verarbeiten und auszuwerten. Zudem sind häufig Modellierungsansätze notwendig, da die gemessenen Größen nicht auf direktem Weg aussagekräftige biomechanische Variablen liefern. Seit wenigen Jahren haben sich hierfür Methoden des maschinellen Lernens als vielversprechende Instrumente zur Ermittlung von Zielvariablen, wie beispielsweise der Gelenkwinkel, herausgestellt. Aktuell befindet sich die Forschung an der Schnittstelle aus Biomechanik, mobiler Sensoren und maschinellem Lernen noch am Anfang. Der Bereich birgt grundsätzlich ein erhebliches Potenzial, um einerseits das Spektrum an mobilen Anwendungen im Sport, insbesondere in Sportarten mit komplexen Bewegungsanforderungen, wie beispielsweise dem Eishockey, zu erweitern. Andererseits können Methoden des maschinellen Lernens zur Abschätzung von Belastungen auf Körperstrukturen mittels mobiler Sensordaten genutzt werden. Vor allem die Anwendung mobiler Sensoren in Kombination mit Prädiktionsmodellen zur Ermittlung der Kniegelenkbelastung, wie beispielsweise der Gelenkmomente, wurde bisher nur unzureichend erforscht. Gleichwohl kommt der mobilen Erfassung von Gelenkbelastungen in der Diagnostik und Rehabilitation von Verletzungen sowie Muskel-Skelett-Erkrankungen eine zentrale Bedeutung zu. Das übergeordnete Ziel dieser Dissertation ist es, festzustellen inwieweit tragbare Sensoren und Verfahren des maschinellen Lernens zur Quantifizierung sportlicher Bewegungsmerkmale sowie zur Ermittlung der Belastung von Körperstrukturen bei der Ausführung von Alltags- und Sportbewegungen eingesetzt werden können. Die Dissertation basiert auf vier Studien, welche in internationalen Fachzeitschriften mit Peer-Review-Prozess erschienen sind. Die ersten beiden Studien konzentrieren sich zum einen auf die automatisierte Erkennung von zeitlichen Events und zum anderen auf die mobile Leistungsanalyse während des Schlittschuhlaufens im Eishockey. Die beiden weiteren Studien präsentieren jeweils einen neuartigen Ansatz zur Schätzung von Belastungen im Kniegelenk mittels künstlich neuronalen Netzen. Zwei mobile Sensoren, welche in eine Kniebandage integriert sind, dienen hierbei als Datenbasis zur Ermittlung von Kniegelenkskräften während unterschiedlicher Sportbewegungen sowie von Kniegelenksmomenten während verschiedener Lokomotionsaufgaben. Studie I zeigt eine präzise, effiziente und einfache Methode zur zeitlichen Analyse des Schlittschuhlaufens im Eishockey mittels einem am Schlittschuh befestigten Beschleunigungssensor. Die Validierung des neuartigen Ansatzes erfolgt anhand synchroner Messungen des plantaren Fußdrucks. Der mittlere Unterschied zwischen den beiden Erfassungsmethoden liegt sowohl für die Standphasendauer als auch der Gangzyklusdauer unter einer Millisekunde. Studie II zeigt das Potenzial von Beschleunigungssensoren zur Technik- und Leistungsanalyse des Schlittschuhlaufens im Eishockey. Die Ergebnisse zeigen für die Standphasendauer und Schrittintensität sowohl Unterschiede zwischen beschleunigenden Schritten und Schritten bei konstanter Geschwindigkeit als auch zwischen Teilnehmern unterschiedlichen Leistungsniveaus. Eine Korrelationsanalyse offenbart, insbesondere für die Schrittintensität, einen starken Zusammenhang mit der sportlichen Leistung des Schlittschuhlaufens im Sinne einer verkürzten Sprintzeit. Studie III präsentiert ein tragbares System zur Erfassung von Belastungen im Kniegelenk bei verschiedenen sportlichen Bewegungen auf Basis zweier mobiler Sensoren. Im Speziellen werden unterschiedliche lineare Bewegungen, Richtungswechsel und Sprünge betrachtet. Die mittels künstlich neuronalem Netz ermittelten dreidimensionalen Kniegelenkskräfte zeigen, mit Ausnahme der mediolateralen Kraftkomponente, für die meisten analysierten Bewegungen eine gute Übereinstimmung mit invers-dynamisch berechneten Referenzdaten. Die abschließende Studie IV stellt eine Erweiterung des in Studie III entwickelten tragbaren Systems zur Ermittlung von Belastungen im Kniegelenk dar. Die ambulante Beurteilung der Gelenkbelastung bei Kniearthrose steht hierbei im Fokus. Die entwickelten Prädiktionsmodelle zeigen für das Knieflexionsmoment eine gute Übereinstimmung mit invers-dynamisch berechneten Referenzdaten für den Großteil der analysierten Bewegungen. Demgegenüber ist bei der Ermittlung des Knieadduktionsmoments mittels künstlichen neuronalen Netzen Vorsicht geboten. Je nach Bewegung, kommt es zu einer schwachen bis starken Übereinstimmung zwischen der mittels Prädiktionsmodell bestimmten Belastung und dem Referenzwert. Zusammenfassend tragen die Ergebnisse von Studie I und Studie II zur sportartspezifischen Leistungsanalyse im Eishockey bei. Zukünftig können sowohl die Trainingsqualität als auch die gezielte Verbesserung sportlicher Leistung durch den Einsatz von am Körper getragener Sensoren in hohem Maße profitieren. Die methodischen Neuerungen und Erkenntnisse aus Studie III und Studie IV ebnen den Weg für die Entwicklung neuartiger Technologien im Gesundheitsbereich. Mit Blick in die Zukunft können mobile Sensoren zur intelligenten Analyse menschlicher Bewegungen sinnvoll eingesetzt werden. Die vorliegende Dissertation zeigt, dass die mobile Bewegungsanalyse zur Erleichterung der sportartspezifischen Leistungsdiagnostik unter Feldbedingungen beiträgt. Zudem zeigt die Arbeit, dass die mobile Bewegungsanalyse einen wichtigen Beitrag zur Verbesserung der Gesundheitsdiagnostik und Rehabilitation nach akuten Verletzungen oder bei chronischen muskuloskelettalen Erkrankungen leistet

Sit-to-Stand Phases Detection by Inertial Sensors

The Sit-to-Stand(STS) is defined as the transition from the sitting to standing position. It is commonly adopted in clinical practice because musculoskeletal or neurological degenerative disorders, as well as the natural process of ageing, deter-mine an increased difficulty in rising up from a seated position. This study aimed to detect the Sit To Stand phases using data from inertial sensors. Due to the high variability of this movement, and, consequently the difficulty to define events by thresholds, we used the machine learning. We collected data from 27 participants (13 females,24.37\ub13.32 years old). They wore 10 Inertial Sensors placed on: trunk,back(L4-L5),left and right thigh, tibia, and ankles. The par-ticipants were asked to stand from an height adjustable chair for 10 times. The STS exercises were recorded separately. The starting and ending points of each phase were identified by key events. The pre-processing included phases splitting in epochs. The features extracted were: mean, standard deviation, RMS, Max and min, COV and first derivative. The features were on the epochs for each sensor. To identify the most fitting classifier, two classifier algorithms,K-nearest Neighbours( KNN) and Support Vector Machine (SVM) were trained. From the data recorded, four dataset were created varying the epochs duration, the number of sensors. The validation model used to train the classifier. As validation model, we compared the results of classifiers trained using Kfold and Leave One Subject out (LOSO) models. The classifier performances were evaluated by confusion matrices and the F1 scores. The classifiers trained using LOSO technique as validation model showed higher values of predictive accuracy than the ones trained using Kfold. The predictive accuracy of KNN and SVM were reported below: \u2022 KFold \u2013 mean of overall predictive accuracy KNN: 0.75; F1 score: REST 0.86, TRUNK LEANING 0.35,STANDING 0.60,BALANCE 0.54, SITTING 0.55 \u2013 mean of overall predictive accuracy SVM: 0.75; F1 score: REST 0.89, TRUNK LEANING 0.48,STANDING 0.48,BALANCE 0.59, SITTING 0.62 \u2022 LOSO \u2013 mean of overall predictive accuracy KNN: 0.93; F1 score: REST 0.96, TRUNK LEANING 0.79,STANDING 0.89,BALANCE 0.95, SITTING 0.88 \u2013 mean of overall predictive accuracy SVM: 0.95; F1 score phases: REST 0.98, TRUNK LEANING 0.86,STANDING 0.91,BALANCE 0.98, SIT-TING 0.9