Ubitrack: A Study on Lost Person Activity Estimation Using Accelerometer Data from Smartphones

As smartphones become very more popular, applications are being developed with new and innovative ways to solve problems faced in the day-to-day lives of users. One area of smartphone technology that has been developed in recent years is human activity recognition HAR. This technology uses various sensors that are built into the smartphone to sense a person\u27s activity in real time. Applications that incorporate HAR can be used to track a person\u27s movements and are very useful in areas such as health care. In our research, we use this type of motion sensing technology, specifically, using data collected from the accelerometer sensor. The purpose of this study is to estimate the pilgrim who may become lost on the annual pilgrimage to Hajj. The application is capable of estimating the movements of people in a crowded area, and of indicating whether or not the person is lost in a crowded area based on his/her movements as detected by the smartphone. This will be a great benefit to anyone interested in crowd management strategies, specifically regarding Hajj. In this thesis, we review related literature and research that has given us the basis for our own research. For example, we could not create this application without the use of HAR technology and without specific classification algorithms. We also detail research on lost person behavior. We looked at the typical movements a person will likely make when he/she is lost and used these movements to indicate lost person behavior. We then describe the creation of the application, all of its components, and the testing process. Finally, we discuss the results of our trials and plans for future work

Real-Time Traffic Safety Evaluation in the Context of Connected Vehicles and Mobile Sensing

Recently, with the development of connected vehicles and mobile sensing technologies, vehicle-based data become much easier to obtain. However, only few studies have investigated the application of this kind of novel data to real-time traffic safety evaluation. This dissertation aims to conduct a series of real-time traffic safety studies by integrating all kinds of available vehicle-based data sources. First, this dissertation developed a deep learning model for identifying vehicle maneuvers using data from smartphone sensors (i.e., accelerometer and gyroscope). The proposed model was robust and suitable for real-time application as it required less processing of smartphone sensor data compared with the existing studies. Besides, a semi-supervised learning algorithm was proposed to make use of the massive unlabeled sensor data. The proposed algorithm could alleviate the cost of data preparation and improve model transferability. Second, trajectory data from 300 buses were used to develop a real-time crash likelihood prediction model for urban arterials. Results from extensive experiments illustrated the feasibility of using novel vehicle trajectory data to predict real-time crash likelihood. Moreover, to improve the model\u27s performance, data fusion techniques were proposed to integrated trajectory data from various vehicle types. The proposed data fusion techniques significantly improved the accuracy of crash likelihood prediction in terms of sensitivity and false alarm rate. Third, to improve pedestrian and bicycle safety, different vehicle-based surrogate safety measures, such as hard acceleration, hard deceleration, and long stop, were proposed for evaluating pedestrian and bicycle safety using vehicle trajectory data. In summary, the results from this dissertation can be further applied to real-time safety applications (e.g., real-time crash likelihood prediction and visualization system) in the context of proactive traffic management

Smartphone-based vehicle telematics: a ten-year anniversary

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordJust as it has irrevocably reshaped social life, the fast growth of smartphone ownership is now beginning to revolutionize the driving experience and change how we think about automotive insurance, vehicle safety systems, and traffic research. This paper summarizes the first ten years of research in smartphone-based vehicle telematics, with a focus on user-friendly implementations and the challenges that arise due to the mobility of the smartphone. Notable academic and industrial projects are reviewed, and system aspects related to sensors, energy consumption, and human-machine interfaces are examined. Moreover, we highlight the differences between traditional and smartphone-based automotive navigation, and survey the state of the art in smartphone-based transportation mode classification, vehicular ad hoc networks, cloud computing, driver classification, and road condition monitoring. Future advances are expected to be driven by improvements in sensor technology, evidence of the societal benefits of current implementations, and the establishment of industry standards for sensor fusion and driver assessment

Classifying road surfaces using smarphone accelerometers for informed road transportation

Undergraduate thesis submitted to the Department of Computer Science, Ashesi University, in partial fulfillment of Bachelor of Science degree in / Computer Science, May 2020Road navigation applications such as Google Maps and Apple Maps provide routing information to their continuously increasing number of users, enabling them to get from one destination to another. These applications provide information such as routes and traffic conditions which influence the time taken to travel by the user of the information. However, these navigation services are lacking in providing road surface quality information. Road surface quality information of a route not only influences the time taken to travel the route, but also provide salient information on the comfort of travel for the passenger and the effect the terrain will have on the vehicle. This work builds on previous work by further developing and characterizing a Logistic Regression (LR) algorithm for classifying road surface quality using accelerometer data sourced from mobile devices in moving vehicles along four different types of roads: very good, good, bad, and very bad roads.Ashesi Universit

Weighted aggregation in the domain of crowd-based road condition monitoring

This paper focuses on crowd-based road condition monitoring using smart devices, such as smartphones and evaluates different strategies for aggregating multiple measurements (arithmetic mean and weighted means using R2 and RMSE) for predicting the longitudinal road roughness. The results confirm that aggregating predictions from single drives leads to a higher model performance. This has been expected and confirms the intuition. The overall R2 could be increased from 0.69 to 0.75 on average and the NRMSE could be decreased from 9% to 8% on average. However, contrary to the intuition, the results show that weighted aggregations of single predictions should be avoided, which is consistent with previous findings in other domains, such as financial forecasting

Context Aware Computing or the Sense of Context

ITALIANO: I sistemi ubiquitous e pervasivi, speciali categorie di sistemi embedded (immersi), possono essere utilizzati per rilevare il contesto che li circonda. In particolare, i sistemi context-aware sono in grado di alterare il loro stato interno e il loro comportamento in base all’ambiente (context) che percepiscono. Per aiutare le persone nell’espletare le proprie attivitá, tali sistemi possono utilizzare le conoscenze raccolte attorno a loro. Un grande sforzo industriale e di ricerca, orientato all’innovazione dei sensori, processori, sistemi operativi, protocolli di comunicazione, e framework, offre molte tecnologie definibili abilitanti, come le reti di sensori wireless o gli Smartphone. Tuttavia, nonostante tale sforzo significativo, l’adozione di sistemi pervasivi che permettano di migliorare il monitoraggio dello sport, l’allenamento e le tecnologie assistive é ancora piuttosto limitato. Questa tesi individua due fattori determinanti per questo basso utilizzo delle tecnologie pervasive, principalmente relativi agli utenti. Da un lato il tentativo degli esperti e dei ricercatori dell’informatica di indurre l’adozione di soluzioni informatiche, trascurando parzialmente l’interazione con gli utenti finali, dall’altro lato una scarsa attenzione all’interazione tra uomo e computer. Il primo fattore puó essere tradotto nella mancanza di attenzione a ció che é rilevante nel contesto dei bisogni (speciali) dell’utente. Il secondo é rappresentato dall’utilizzo diffuso di interfacce grafiche di presentazione delle informazioni, che richiede un elevato livello di sforzo cognitivo da parte degli utenti. Mentre lo studio della letteratura puó fornire conoscenze sul contesto dell’utente, solo il contatto diretto con lui arricchisce la conoscenza di consapevolezza, fornendo una precisa identificazione dei fattori che sono piú rilevanti per il destinatario dell’applicazione. Per applicare con successo le tecnologie pervasive al campo dello sport e delle tecnologie assistive, l’identificazione dei fattori rilevanti é una premessa necessaria, Tale processo di identificazione rappresenta l’approccio metodologico principale utilizzato per questa tesi. Nella tesi si analizzano diversi sport (canottaggio, nuoto, corsa ) e una disabilitá (la cecitá), per mostrare come la metodologia di investigazione e di progettazione proposta venga messa in pratica. Infatti i fattori rilevanti sono stati identificati grazie alla stretta collaborazione con gli utenti e gli esperti nei rispettivi campi. Si descrive il processo di identificazione, insieme alle soluzioni elaborate su misura per il particolare campo d’uso. L’uso della sonificazione, cioé la trasmissione di informazioni attraverso il suono, si propone di affrontare il secondo problema presentato, riguardante le interfacce utente. L’uso della sonificazione puó facilitare la fruizione in tempo reale delle informazioni sulle prestazioni di attivitá sportive, e puó contribuire ad alleviare parzialmente la disabilitá degli utenti non vedenti. Nel canottaggio, si é identificato nel livello di sincronia del team uno dei fattori rilevanti per una propulsione efficace dell’imbarcazione. Il problema di rilevare il livello di sincronia viene analizzato mediante una rete di accelerometri wireless, proponendo due diverse soluzioni. La prima soluzione é basata sull’indice di correlazione di Pearson e la seconda su un approccio emergente chiamato stigmergia. Entrambi gli approcci sono stati testati con successo in laboratorio e sul campo. Inoltre sono state sviluppate due applicazioni, per smartphone e PC, per fornire la telemetria e la sonificazione del moto di una barca a remi. Nel campo del nuoto é stata condotta una ricerca in letteratura riguardo la convinzione diffusa di considerare la cinematica come il fattore rilevante della propulsione efficace dei nuotatori. Questa indagine ha richiamato l’attenzione sull’importanza di studiare il cosiddetto feel-for-water (sensazione-dell’-acqua) percepito dai nuotatori d’alto livello. É stato progettato un innovativo sistema, per rilevare e comunicare gli effetti fluidodinamici causati dallo spostamento delle masse d’acqua intorno alle mani dei nuotatori. Il sistema é in grado di trasformare la pressione dell’acqua, misurata con sonde Piezo intorno alle mani, in un bio-feedback auditivo, pensato per i nuotatori e gli allenatori, come base per un nuovo modo di comunicare la sensazione-dell’acqua. Il sistema é stato testato con successo nel campo e ha dimostrato di fornire informazioni in tempo reale per il nuotatore e il formatore. Nello sport della corsa sono stati individuati due parametri rilevanti: il tempo di volo e di contatto dei piedi. É stato progettato un sistema innovativo per ottenere questi parametri attraverso un unico accelerometro montato sul tronco del corridore ed é stato implementato su uno smartphone. Per ottenere il risultato voluto é stato necessario progettare e realizzare un sistema per riallineare virtualmente gli assi dell’accelerometro e per estrarre il tempo di volo e di contatto dal segnale dell’accelerometro riallineato. L’applicazione per smartphone completa é stata testata con successo sul campo, confrontando i valori con quelli di attrezzature specializzate, dimostrando la sua idoneitá come ausilio pervasivo all’allenamento di corridori. Per esplorare le possibilitá della sonificazione usata come una base per tecnologia assistiva, abbiamo iniziato una collaborazione con un gruppo di ricerca presso l’Universitá di Scienze Applicate, Ginevra, in Svizzera. Tale collaborazione si é concentrata su un progetto chiamato SeeColOr (See Color with an Orchestra - vedere i colori con un’orchestra). In particolare, abbiamo avuto l’opportunitá di implementare il sistema SeeColOr su smartphone, al fine di consentire agli utenti non vedenti di utilizzare tale tecnologia su dispositivi leggeri e a basso costo. Inoltre, la tesi esplora alcune questioni relative al campo del rilevamento ambientale in ambienti estremi, come i ghiacciai, utilizzando la tecnologia delle Wireless Sensor Networks. Considerando che la tecnologia é simile a quella usata in altri contesti presentati, le considerazioni possono facilmente essere riutilizzate. Si sottolinea infatti che i problemi principali sono legati alla elevata difficoltá e scarsa affidabilitá di questa tecnologia innovativa rispetto alle altre soluzioni disponibili in commercio , definite legacy, basate solitamente su dispositivi piú grandi e costosi, chiamati datalogger. La tesi presenta i problemi esposti e le soluzioni proposte per mostrare l’applicazione dell’approccio progettuale cercato e definito durante lo sviluppo delle attività sperimentali e la ricerca che le ha implementate. ---------------------------------------- ENGLISH: Ubiquitous and pervasive systems, special categories of embedded systems, can be used to sense the context in their surrounding. In particular, context-aware systems are able to alter their internal state and their behaviour based on the context they perceive. To help people in better performing their activities, such systems must use the knowledge gathered about the context. A big research and industrial effort, geared towards the innovation of sensors, processors, operating systems, communication protocols, and frameworks, provides many "enabling" technologies, such as Wireless Sensor Networks or Smartphones. However, despite that significant effort, the adoption of pervasive systems to enhance sports monitoring, training and assistive technologies is still rather small. This thesis identifies two main issues concerning this low usage of pervasive technologies, both mainly related to users. On one side the attempt of computer science experts and researchers to induce the adoption of information technology based solutions, partially neglecting interaction with end users; on the other side a scarce attention to the interaction between humans and computers. The first can be translated into the lack of attention at what is relevant in the context of the user’s (special) needs. The second is represented by the widespread usage of graphical user interfaces to present information, requiring a high level of cognitive effort. While literature studies can provide knowledge about the user’s context, only direct contact with users enriches knowledge with awareness, providing a precise identification of the factors that are more relevant to the user. To successfully apply pervasive technologies to the field of sports engineering and assistive technology, the identification of relevant factors is an obliged premise, and represents the main methodological approach used throughout this thesis. This thesis analyses different sports (rowing, swimming, running) and a disability (blindness), to show how the proposed design methodology is put in practice. Relevant factors were identified thanks to the tight collaboration with users and experts in the respective fields. The process of identification is described, together with the proposed application tailored for the special field. The use of sonification, i.e. conveying information as sound, is proposed to leverage the second presented issue, that regards the user interfaces. The usage of sonification can ease the exploitation of information about performance in real-time for sport activities and can help to partially leverage the disability of blind users. In rowing, the synchrony level of the team was identified as one of the relevant factors for effective propulsion. The problem of detecting the synchrony level is analysed by means of a network of wireless accelerometers, proposing two different solutions. The first solution is based on Pearson’s correlation index and the second on an emergent approach called stigmergy. Both approaches were successfully tested in laboratory and in the field. Moreover two applications, for smartphones and PCs, were developed to provide telemetry and sonification of a rowing boat’s motion. In the field of swimming, an investigation about the widespread belief considering kinematics as the relevant factor of effective propulsion of swimmers drew attention to the importance of studying the so called "feel-for-water" experienced by elite swimmers. An innovative system was designed to sense and communicate fluid-dynamic effects caused by moving water masses around swimmers hands. The system is able to transform water pressure, measured with Piezo-probes, around hands into an auditive biofeedback, to be used by swimmers and trainers, as the base for a new way of communication about the "feel-for-water". The system was successfully tested in the field and proved to provide real-time information for the swimmer and the trainer. In running sports two relevant parameters are time of flight and contact of feet. An innovative system was designed to obtain these parameters using a single trunk mounted accelerometer and was implemented on a smartphone. To achieve the intended result it was necessary to design and implement a system to virtually realign the axes of the accelerometer and to extract time of flight and time of contact phases from the realigned accelerometer signal. The complete smartphone application was successfully tested in the field with specialized equipment, proving its suitability in enhancing training of runners with a pervasive system. To explore possibilities of sonification applied as an assistive technology, we started a collaboration with research group from University of Applied Science, Geneva, Switzerland, focused on a project called SeeColOr (See Color with an Orchestra). In particular we had the opportunity to implement the SeeColOr system on smartphones, in order to enable blind users to use that technology on low cost and lightweight devices. Moreover, the thesis exposes some issues related to a field, environmental sensing in extreme environments, like glaciers, using the innovative Wireless Sensor Networks technology. Considering that the technology is similar to the one used in other presented contexts, learned lessons can easily be reused. It is emphasized that the main problems are related to the high difficulty and low reliability of that innovative technology with respect to other "legacy" commercially available solutions, based on expensive and bigger devices, called dataloggers. The thesis presents the exposed problems and proposed solutions to show the application of the design approach strived during the development and research

Wearable Sensors and Smart Devices to Monitor Rehabilitation Parameters and Sports Performance: An Overview

A quantitative evaluation of kinetic parameters, the joint’s range of motion, heart rate, and breathing rate, can be employed in sports performance tracking and rehabilitation monitoring following injuries or surgical operations. However, many of the current detection systems are expensive and designed for clinical use, requiring the presence of a physician and medical staff to assist users in the device’s positioning and measurements. The goal of wearable sensors is to overcome the limitations of current devices, enabling the acquisition of a user’s vital signs directly from the body in an accurate and non–invasive way. In sports activities, wearable sensors allow athletes to monitor performance and body movements objectively, going beyond the coach’s subjective evaluation limits. The main goal of this review paper is to provide a comprehensive overview of wearable technologies and sensing systems to detect and monitor the physiological parameters of patients during post–operative rehabilitation and athletes’ training, and to present evidence that supports the efficacy of this technology for healthcare applications. First, a classification of the human physiological parameters acquired from the human body by sensors attached to sensitive skin locations or worn as a part of garments is introduced, carrying important feedback on the user’s health status. Then, a detailed description of the electromechanical transduction mechanisms allows a comparison of the technologies used in wearable applications to monitor sports and rehabilitation activities. This paves the way for an analysis of wearable technologies, providing a comprehensive comparison of the current state of the art of available sensors and systems. Comparative and statistical analyses are provided to point out useful insights for defining the best technologies and solutions for monitoring body movements. Lastly, the presented review is compared with similar ones reported in the literature to highlight its strengths and novelties

Acceleration Gait Measures as Proxies for Motor Skill of Walking: A Narrative Review

In adults 65 years or older, falls or other neuromotor dysfunctions are often framed as walking-related declines in motor skill; the frequent occurrence of such decline in walking-related motor skill motivates the need for an improved understanding of the motor skill of walking. Simple gait measurements, such as speed, do not provide adequate information about the quality of the body motion’s translation during walking. Gait measures from accelerometers can enrich measurements of walking and motor performance. This review article will categorize the aspects of the motor skill of walking and review how trunk-acceleration gait measures during walking can be mapped to motor skill aspects, satisfying a clinical need to understand how well accelerometer measures assess gait. We will clarify how to leverage more complicated acceleration measures to make accurate motor skill decline predictions, thus furthering fall research in older adults

State of the art of audio- and video based solutions for AAL

Working Group 3. Audio- and Video-based AAL ApplicationsIt is a matter of fact that Europe is facing more and more crucial challenges regarding health and social care due to the demographic change and the current economic context. The recent COVID-19 pandemic has stressed this situation even further, thus highlighting the need for taking action. Active and Assisted Living (AAL) technologies come as a viable approach to help facing these challenges, thanks to the high potential they have in enabling remote care and support. Broadly speaking, AAL can be referred to as the use of innovative and advanced Information and Communication Technologies to create supportive, inclusive and empowering applications and environments that enable older, impaired or frail people to live independently and stay active longer in society. AAL capitalizes on the growing pervasiveness and effectiveness of sensing and computing facilities to supply the persons in need with smart assistance, by responding to their necessities of autonomy, independence, comfort, security and safety. The application scenarios addressed by AAL are complex, due to the inherent heterogeneity of the end-user population, their living arrangements, and their physical conditions or impairment. Despite aiming at diverse goals, AAL systems should share some common characteristics. They are designed to provide support in daily life in an invisible, unobtrusive and user-friendly manner. Moreover, they are conceived to be intelligent, to be able to learn and adapt to the requirements and requests of the assisted people, and to synchronise with their specific needs. Nevertheless, to ensure the uptake of AAL in society, potential users must be willing to use AAL applications and to integrate them in their daily environments and lives. In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness. Indeed, cameras and microphones are far less obtrusive with respect to the hindrance other wearable sensors may cause to one’s activities. In addition, a single camera placed in a room can record most of the activities performed in the room, thus replacing many other non-visual sensors. Currently, video-based applications are effective in recognising and monitoring the activities, the movements, and the overall conditions of the assisted individuals as well as to assess their vital parameters (e.g., heart rate, respiratory rate). Similarly, audio sensors have the potential to become one of the most important modalities for interaction with AAL systems, as they can have a large range of sensing, do not require physical presence at a particular location and are physically intangible. Moreover, relevant information about individuals’ activities and health status can derive from processing audio signals (e.g., speech recordings). Nevertheless, as the other side of the coin, cameras and microphones are often perceived as the most intrusive technologies from the viewpoint of the privacy of the monitored individuals. This is due to the richness of the information these technologies convey and the intimate setting where they may be deployed. Solutions able to ensure privacy preservation by context and by design, as well as to ensure high legal and ethical standards are in high demand. After the review of the current state of play and the discussion in GoodBrother, we may claim that the first solutions in this direction are starting to appear in the literature. A multidisciplinary 4 debate among experts and stakeholders is paving the way towards AAL ensuring ergonomics, usability, acceptance and privacy preservation. The DIANA, PAAL, and VisuAAL projects are examples of this fresh approach. This report provides the reader with a review of the most recent advances in audio- and video-based monitoring technologies for AAL. It has been drafted as a collective effort of WG3 to supply an introduction to AAL, its evolution over time and its main functional and technological underpinnings. In this respect, the report contributes to the field with the outline of a new generation of ethical-aware AAL technologies and a proposal for a novel comprehensive taxonomy of AAL systems and applications. Moreover, the report allows non-technical readers to gather an overview of the main components of an AAL system and how these function and interact with the end-users. The report illustrates the state of the art of the most successful AAL applications and functions based on audio and video data, namely (i) lifelogging and self-monitoring, (ii) remote monitoring of vital signs, (iii) emotional state recognition, (iv) food intake monitoring, activity and behaviour recognition, (v) activity and personal assistance, (vi) gesture recognition, (vii) fall detection and prevention, (viii) mobility assessment and frailty recognition, and (ix) cognitive and motor rehabilitation. For these application scenarios, the report illustrates the state of play in terms of scientific advances, available products and research project. The open challenges are also highlighted. The report ends with an overview of the challenges, the hindrances and the opportunities posed by the uptake in real world settings of AAL technologies. In this respect, the report illustrates the current procedural and technological approaches to cope with acceptability, usability and trust in the AAL technology, by surveying strategies and approaches to co-design, to privacy preservation in video and audio data, to transparency and explainability in data processing, and to data transmission and communication. User acceptance and ethical considerations are also debated. Finally, the potentials coming from the silver economy are overviewed.publishedVersio

IMUs: validation, gait analysis and system’s implementation

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)Falls are a prevalent problem in actual society. The number of falls has been increasing greatly in the last fifteen years. Some falls result in injuries and the cost associated with their treatment is high. However, this is a complex problem that requires several steps in order to be tackled. Namely, it is crucial to develop strategies that recognize the mode of locomotion, indicating the state of the subject in various situations, namely normal gait, step before fall (pre-fall) and fall situation. Thus, this thesis aims to develop a strategy capable of identifying these situations based on a wearable system that collects information and analyses the human gait. The strategy consists, essentially, in the construction and use of Associative Skill Memories (ASMs) as tools for recognizing the locomotion modes. Consequently, at an early stage, the capabilities of the ASMs for the different modes of locomotion were studied. Then, a classifier was developed based on a set of ASMs. Posteriorly, a neural network classifier based on deep learning was used to classify, in a similar way, the same modes of locomotion. Deep learning is a technique actually widely used in data classification. These classifiers were implemented and compared, providing for a tool with a good accuracy in recognizing the modes of locomotion. In order to implement this strategy, it was previously necessary to carry out extremely important support work. An inertial measurement units’ (IMUs) system was chosen due to its extreme potential to monitor outpatient activities in the home environment. This system, which combines inertial and magnetic sensors and is able to perform the monitoring of gait parameters in real time, was validated and calibrated. Posteriorly, this system was used to collect data from healthy subjects that mimicked Fs. Results have shown that the accuracy of the classifiers was quite acceptable, and the neural networks based classifier presented the best results with 92.71% of accuracy. As future work, it is proposed to apply these strategies in real time in order to avoid the occurrence of falls.As quedas são um problema predominante na sociedade atual. O número de quedas tem aumentado bastante nos últimos quinze anos. Algumas quedas resultam em lesões e o custo associado ao seu tratamento é alto. No entanto, trata-se de um problema complexo que requer várias etapas a serem abordadas. Ou seja, é crucial desenvolver estratégias que reconheçam o modo de locomoção, indicando o estado do sujeito em várias situações, nomeadamente, marcha normal, passo antes da queda (pré-queda) e situação de queda. Assim, esta tese tem como objetivo desenvolver uma estratégia capaz de identificar essas situações com base num sistema wearable que colete informações e analise a marcha humana. A estratégia consiste, essencialmente, na construção e utilização de Associative Skill Memories (ASMs) como ferramenta para reconhecimento dos modos de locomoção. Consequentemente, numa fase inicial, foram estudadas as capacidades das ASMs para os diferentes modos de locomoção. Depois, foi desenvolvido um classificador baseado em ASMs. Posteriormente, um classificador de redes neuronais baseado em deep learning foi utilizado para classificar, de forma semelhante, os mesmos modos de locomoção. Deep learning é uma técnica bastante utilizada em classificação de dados. Estes classificadores foram implementados e comparados, fornecendo a uma ferramenta com uma boa precisão no reconhecimento dos modos de locomoção. Para implementar esta estratégia, era necessário realizar previamente um trabalho de suporte extremamente importante. Um sistema de unidades de medição inercial (IMUs), foi escolhido devido ao seu potencial extremo para monitorizar as atividades ambulatórias no ambiente domiciliar. Este sistema que combina sensores inerciais e magnéticos e é capaz de efetuar a monitorização de parâmetros da marcha em tempo real, foi validado e calibrado. Posteriormente, este Sistema foi usado para adquirir dados da marcha de indivíduos saudáveis que imitiram quedas. Os resultados mostraram que a precisão dos classificadores foi bastante aceitável e o classificador baseado em redes neuronais apresentou os melhores resultados com 92.71% de precisão. Como trabalho futuro, propõe-se a aplicação destas estratégias em tempo real de forma a evitar a ocorrência de quedas