Inertial measurement units (IMUs) are devices that sense accelerations and angular rates in 3D so that vehicles and other devices can estimate their orientations, positions, and velocities. While traditionally large, heavy, and costly, using mechanical gyroscopes and stabilized platforms, the recent development of micro-electromechanical sensor (MEMS) IMUs that are small, light, and inexpensive has led to their adoption in many everyday systems such as cell phones, video game controllers, and commercial drones. MEMS IMUs, despite their advantages, have major drawbacks when it comes to accuracy and reliability. The idea of using more than one of these sensors in an array, instead of using only one, and fusing their outputs to generate an improved solution is explored in this thesis.

The analysis of human movement is important for diagnosis of as wellas planning and evaluating treatments of disorders or injuries affectingmovement. Optical motion capture combined with force plates provideaccurate measurements, but are confined to laboratory settings limiting theirpotential usefulness in clinical applications. Efforts are made to movemeasurements out of the laboratory making them more accessible, cheaperand easier to use for healthcare providers. This work aimed to assess thefeasibility of doing motion analysis with a wearable system consisting ofIMUs and pressure insole sensors, while also developing a methodology thatcould be used for subsequent validation. Six subjects performed walking, sideskipping, squats, chair stands and a balance exercise, while data was collectedsimultaneously from the wearable system and optical motion capture withforce plates. For demonstration, data from one example subject was analysedand included in this work. The wearable system showed promising results formeasuring ground reaction force. Center of pressure errors were relativelyhigh, likely influenced by the choice of method for coordinate transformationbetween the systems. Joint angle errors varied from low to very high fordifferent trials. Ankle dorsiflexion angle showed low errors and pelvis tiltangle high errors for all motion types. There is a need to investigate thecause for these high errors before more measurements are conducted. Themethodology presented in this work can, with a few recommended changes,be used for future validation of the wearable motion analysis system.

Occupational upper extremity disorders have become a major issue in modern society. Poorly designed workplaces, high job demands, and incorrect work-habits can lead to the development of upper extremity disorders (UEDs) in the workplace. This issue not only causes health-relatedproblems for the individual but also forms a significant economic burden on society due to sickleaves, healthcare and untimely exit of affected individuals from the workforce. The risk of developing occupational UEDs varies with different professions. The European Agency for Safety and Health at Work (EU-OSHA) has recognized significant occupational health risks associated with the hairdressing profession. It has been estimated that UEDs are five times more prevalent amongst hairdressers than other professions. Qualitative risk assessment tools based on self-reports and observation have been used to identify the risks of developing UEDs with hairdressing profession before. However, a quantitative risk assessment tool that provides objective data on work posture is more precise and objective than self-report and observation. This data can help to identify the risks of developing UEDs associated with each hairdressing task. Furthermore, it can enable self-assessment of workload and posture awareness by providing feedback to the user. Inertial Measurement Units (IMU) as part of a wearable system developed at KTH were used in this study to investigate the risks of developing UEDs for hairdressing students. The feasibility of using a feedback function for providing posture awareness was also evaluated by comparing the measurements obtained with and without using the feedback function. Twelve hairdresser students were enrolled in the study. The percentage of time for elevated angles above 30°, 60° and 90° for arms, and above 45° or less than 0° for the trunk flexion is presented. In addition, 10th and 90th percentiles (°) of arms and trunk angular distribution is presented. The result of a statistical analysis performed on data with and without feedback was used to evaluate the effectivity of using the feedback function in preventing the development of occupational UEDs. A System Usability Scale (SUS) questionnaire was used to evaluate the overall usability of the system. The result of this study confirms that the hairdressing profession falls in the high-risk category for developing UEDs. The use of this technical system has enabled a precise risk assessment evaluation of each hairdressing task. Such data can be used as a foundation for improving the ergonomic design of the workplace. The feasibility of using the feedback function as a prevention tool on the individual level is highly dependent on the individuals’ motivation and their attitude towards changing their work habits. However, the results in general, indicate a decrease in the abduction angle (°) for both left and right arm when the feedback function is used. For example, the 90th percentile abduction angles (°) for left arm (all 12 subjects) during the drying part of one fundamental work-cycle decreased from a value of 60.4° to 58.2° when the feedback function was used. The 90th percentile abduction angles (°) for the right arm during the same part of the fundamental work-cycle decreased from an angle of 53.1° to 51.4°. The SUS score of 75.6 indicates good overall usability for the system. / Besvär i det muskuloskeletala systemet i överkroppen som uppkommer på grund av påfrestande arbetsställningar och icke-optimala arbetsvanor blir allt vanligare i det moderna samhället. Besvären orsakar inte bara hälsorelaterade problem för individen utan även en avsevärd ekonomisk börda för samhället. Risken för att utveckla skador i överkroppen varierar med olika yrken. Europeiska arbetsmiljöbyrån (EU-OSHA) har identifierat betydande hälsorisker i samband med frisörarbete. Det har uppskattats att besvär i överkroppen är 5 gånger mer förekommande hos frisörer jämfört med andra yrken. Det finns många forskningsprojekt som har använt kvalitativa riskbedömningsverktyg, baserade på självrapportering och observation, som identifierar riskerna med att utveckla skador i överkroppen bland frisörer. Ett kvantitativt riskbedömningsverktyg som ger objektiva data om arbetsställning är dock mer exakt än självrapportering och observation. Ett sådant verktyg kan hjälpa till att identifiera risken för skadeutveckling i överkroppen. Inertial Measurement Units (IMUs) är en del av ett bärbart mätsystem som har utvecklats påKTH. Systemet användes i denna studie för att identifiera risken för skadeutveckling i överkroppen bland frisörer. Riskidentifieringen gjordes genom att mäta vinkel på armar och rygg. Mätsystemet har även en inbyggd återkopplingsfunktion som uppmärksammar användaren om deras kroppsställning. Effektiviteten av att använda återkopplingsfunktionen för att förebygga jobbrelaterade skador utvärderades genom jämförelse av mätningar som erhållits med och utan återkopplingsfunktion. Tolv frisörstudenter deltog i studien. Överkroppspositionen definierades av vinklar över 45° eller mindre än 0° från en position där ryggen är rak. Abduktionsvinklar över 30°, 60° och 90° mättes för armar. Tidsperioden för dessa vinklar d.v.s. hur lång tid överkroppen hölls i dessa vinklar räknades. Armar och överkroppvinklar för 10:e och 90:e percentilen (°) samt resultat av en statistisk analys som utfördes på data samlade med och utan återkopplingsfunktionen presenterades. Analysen utfördes för att utvärdera hur effektiv återkopplingsfunktionen är för att förhindra arbetsskadeutveckling. En System Usability Scale (SUS) frågeformulär användes för att utvärdera systemets övergripande användbarhet.Resultatet av denna studie bekräftar att frisöryrket faller i högriskkategorin för arbetsskadeutveckling. Användningen av detta bärbara mätsystem har möjliggjort en exakt riskbedömning för olika arbetsuppgifter. En sådan information kan användas som grund för att förbättra ergonomiska förhållanden på arbetsplatser. Effektiviteten av återkopplingsfunktionen som ett förebyggande verktyg på individnivå är starkt beroende av individernas motivation och deras inställning till att ändra sina arbetsvanor. Emellertid anger resultaten en generell minskning av armvinklar (°) för både vänster och höger arm när återkopplingsfunktionen används. Till exempel har den 90:e percentil vinklarna (°) för vänsterarm (alla 12 personer) under hög belastning minskat från ett värde av 60.4° till 58.2 °. Den 90:e percentil vinklarna (°)för höger arm under hög belastning har också minskat från ett värde av 53.1° till 51.4°. SUS-poängen på 75.6 indikerar en bra användbarhet för systemet

Physiotherapy is a key part of treatment for neurological and musculoskeletal disorders, which affect millions in the U.S. each year. Physical therapy treatments typically consist of an initial diagnostic session during which patients’ impairments are assessed and exercises are prescribed to improve the impaired functions. As part of the treatment program, exercises are often assigned to be performed at home daily. Patients return to the clinic weekly or biweekly for check-up visits during which the physical therapist reassesses their condition and makes further treatment decisions, including readjusting the exercise prescriptions. Most physical therapists work in clinics or hospitals. When patients perform their exercises at home, physical therapists cannot supervise them and lack quantitative exercise data reflecting the patients’ exercise compliance and performance. Without this information, it is difficult for physical therapists to make informed decisions or treatment adjustments. To make informed decisions, physical therapists need to know how often patients exercise, the duration and/or repetitions of each session, exercise metrics such as the average velocities and ranges of motion for each exercise, patients’ symptom levels (e.g. pain or dizziness) before and after exercise, and what mistakes patients make. In this thesis, I evaluate and work towards a solution to this problem. The growing ubiquity of mobile and wearable technology makes possible the development of “virtual rehabilitation assistants.” Using motion sensors such as accelerometers and gyroscopes that are embedded in a wearable device, the “assistant” can mediate between patients at home and physical therapists in the clinic. Its functions are to:  use motion sensors to record home exercise metrics for compliance and performance and report these metrics to physical therapists in real-time or periodically;  allow physical therapists and patients to quantify and see progress on a fine-grain level;  record symptom levels to further help physical therapists gauge the effectiveness of exercise prescriptions;  offer real-time mistake recognition and feedback to the patients during exercises; One contribution of this thesis is an evaluation of the feasibility of this idea in real home settings. Because there has been little research on wearable virtual assistants in patient homes, there are many unanswered questions regarding their use and usefulness: Q1. What patient in-home data could wearable virtual assistants gather to support physical therapy treatments? Q2. Can patient data gathered by virtual assistants be useful to physical therapists? 3 Q3. How is this wearable in-home technology received by patients? I sought to answer these questions by implementing and deploying a prototype called “SenseCap.” SenseCap is a small mobile device worn on a ball cap that monitors patients’ exercise movements and queries them about their symptoms. A technology probe study showed that the virtual assistant could gather important compliance, performance, and symptom data to assist physical therapists’ decision-making, and that this technology would be feasible and acceptable for in-home use by patients. Another contribution of this thesis is the development of a tool to allow physical therapists to create and customize virtual assistants. With current technology, virtual assistants require engineering and programming efforts to design, implement, configure and deploy them. Because most physical therapists do not have access to an engineering team they and their patients would be unable to benefit from this technology. With the goal of making virtual assistants accessible to any physical therapist, I explored the following research questions: Q4. Would a user-friendly rule-specification interface make it easy for physical therapists to specify correct and incorrect exercise movements directly to a computer? What are the limitations of this method of specifying exercise rules? Q5. Is it possible to create a CAD-type authoring tool, based on a usable interface, that physical therapists could use to create their own customized virtual assistant for monitoring and coaching patients? What are the implementation details of such a system and the resulting virtual assistant? Q6. What preferences do PTs have regarding the delivery of coaching feedback for patients? Q7. What is the recognition accuracy of a virtual rehabilitation assistant created by this tool? This dissertation research aims to improve our understanding of the barriers to rehabilitation that occur because of the invisibility of home exercise behavior, to lower these barriers by making it possible for patients to use a widely-available and easily-used wearable device that coaches and monitors them while they perform their exercises, and improve the ability of physical therapists to create an exercise regime for their patients and to learn what patients have done to perform these exercises. In doing so, treatment should be better suited to each patient and more successful.

Dissertação (mestrado)—Universidade de Brasília, Centro de Desenvolvimento Sustentável, Programa de Pós-Graduação em Desenvolvimento Sustentável, 2017. / Submitted by Raquel Viana (raquelviana@bce.unb.br) on 2018-05-11T18:15:25Z No. of bitstreams: 1 2017_DanielMorenoJiménez.pdf: 10853446 bytes, checksum: 25a8c4b69822701c7e46f006669609f3 (MD5) / Approved for entry into archive by Raquel Viana (raquelviana@bce.unb.br) on 2018-05-11T18:17:58Z (GMT) No. of bitstreams: 1 2017_DanielMorenoJiménez.pdf: 10853446 bytes, checksum: 25a8c4b69822701c7e46f006669609f3 (MD5) / Made available in DSpace on 2018-05-11T18:17:58Z (GMT). No. of bitstreams: 1 2017_DanielMorenoJiménez.pdf: 10853446 bytes, checksum: 25a8c4b69822701c7e46f006669609f3 (MD5) Previous issue date: 2018-05-10 / A cidade de Medellín na Colômbia foi escolhida como a cidade mais inovadora no ano 2013. O reconhecimento foi principalmente por suas soluções em transporte, redução de emissões de CO2 e redução da criminalidade. No âmbito da mobilidade e sustentabilidade, a cidade de Medellín apresenta ainda pontos a serem melhorados. O objetivo desta dissertação é analisar o padrão de mobilidade urbana na área metropolitana de Medellín (Colômbia) por meio da aplicação do Índice de Mobilidade Urbana Sustentável (IMUS). O IMUS desenvolvido por COSTA (2008) possui uma visão sistêmica necessária para a sustentabilidade da mobilidade urbana, já que envolve, de alguma maneira, os pilares da sustentabilidade (Ambiental, social e econômico), com um sistema de domínios que interliga as ações tomadas num âmbito com as consequências de um outro ou ao invés. A pesquisa foi desenvolvida em quatro etapas: Levantamento de informação secundária e revisão bibliográfica, contextualização da área de estudo, cálculo do IMUS para a cidade com informações, tanto primarias quanto secundarias e analise dos indicadores para cada domínio. Na fase final se analisou a sensibilidade do índice respeito aos projetos em execução e o domínio com maior peso do índice. Os resultados obtidos mostram que a cidade efetivamente tem pontos a favor na inovação, sobre todo na área de infraestrutura e transporte urbano. Comparado com outras cidades (Brasileiras) nas que já foi calculado o IMUS, os resultados mostram um índice de aproximadamente do dobro do valor do indice. Também conseguiu se concluir que o IMUS, além de ser uma ferramenta que facilita a compreensão de fenômenos interconectados, pode ser usado em outros contextos geográficos, políticos e sociais. / Medellín city in Colombia was chosen as the most innovative city in the year 2013. The recognition was mainly for its solutions in transport, reduction of CO2 emissions and reduction of crime. In terms of mobility and sustainability, the city of Medellín also has points to improve. The objective of this dissertation is to analyze the urban mobility pattern in the metropolitan area of Medellín (Colombia) by applying the Urban Sustainable Mobility Index (IMUS). The IMUS developed by COSTA (2008) has a systemic vision necessary for the sustainability of urban mobility, since it involves in some way the pillars of sustainability (Environmental, social and economic) with a system of domains that interconnects the actions taken in a the consequences of another or rather. The research was developed in four stages: Survey of secondary information and bibliographic review, contextualization of the study area, calculation of the IMUS for the city with both primary and secondary information and analysis of the indicators for each domain. In the final phase, the sensitivity of the index regarding the projects in execution and the domain with greater weight of the index was analyzed. The results obtained show that the city has indeed favorable points in innovation, especially in the area of infrastructure and urban transport. Compared with other cities (Brazilian) in which the IMUS has already been calculated, the results show an index of approximately double. It has also been concluded that IMUS, besides being a tool that facilitates the understanding of interconnected phenomena, can be used in other geographic, political and social contexts.

Acquiring joint kinematics, joint moments, and ground reaction forces (GRFs) during walking is essential for assessing disease progression and health monitoring during rehabilitation. However, spatial and temporal constraints, expert processing, and high costs limit the current gold standard methods, such as optical motion capture systems and floor-embedded force plates. Experts have suggested wearables with machine learning methods to address this issue, but their large sensor count renders them impractical for daily use, and the use of generic algorithms limits their accuracy. As a result, learning kinematics and kinetics in everyday life outside of laboratory settings is challenging. Thus, there is a need for an inexpensive, near-real-time system and an accurate method for estimating kinematics, joint moments, and GRFs. This dissertation proposes using shoe-mounted IMU sensors and deep learning to estimate these parameters across various locomotion modes, reflecting everyday walking conditions. Four different approaches are explored. The first approach uses shoe-embedded IMU sensors with novel deep learning models, DeepBBWAE-Net, Kinetics-FM-DLR-Ensemble-Net, and DL-Kinetics-FM-Net, which outperform state-of-the-art models but are computationally expensive. The second approach introduces Kinematics-Net and Kinetics-MMF-Net, which are lightweight yet maintain similar performance. Sparse IMU sensors on the feet may miss critical walking dynamics, so the third approach proposes a sensor distillation technique, transferring knowledge from a teacher model (trained with full sensors) to a student model (trained with sparse IMUs), enhancing estimation accuracy. Although our models are trained on a substantial number of subjects, deep learning models tend to perform better with larger datasets. Collecting extensive subject data is resource-intensive and time-consuming. Additionally, public datasets often differ in sensor types, locations, and protocols. Our fourth approach addresses this by proposing a domain adaptation technique that transfers knowledge from source datasets to the target dataset, improving performance in the target domain.

<p>Civil engineering structures must provide an adequate and safe performance during their time of service, and the owners of these structures must have a reliable inspection strategy to ensure time-dependent damage does not become excessive. Visual inspection is the first step in every structural inspection; however, many elements in the majority of structures are difficult to access and require specialized personal and equipment. In an attempt to reduce the risk of the inspector and the cost of additional equipment, the use of Unmanned Aircraft Systems (UAS) has been increasing in the last years. The absence of standards and regulations regarding the use of UAS in inspection of structures has allowed the market to widely advertise Unmanned Aerial Vehicles (UAV) without protocols or qualifications that prove their effectiveness, leaving the owners of the structures to solely rely on claims of the vendors before deciding which technology suits their particular inspection needs. Focusing primarily on bridge inspection, this research aimed to address the lack of performance-based evaluation and standards for UAS, developing a validation criterion to evaluate a given UAS based on a repeatable test that resembles typical conditions in a structure. </p><p><br></p><p>Current applications of UAS in inspection of structures along with its advantages and limitations were studied to determine the current status of UAS technologies. A maximum typical rotor-tip-to-rotor-tip distance of an UAV was determined based on typical UAVs used in bridge inspection, and two main parameters were found to be relevant when flying close to structures: proximity effects in the UAV and availability of visual line of sight. Distances where proximity effects are relevant were determined based on several field inspections and flights close to structures. In addition, the use of supplementary technologies such as Global Positioning System (GPS) and Inertial Measurement Units (IMU) was studied to understand their effect during inspection. </p><p><br></p><p>Following the analysis, the author introduces the idea of a series of obstacles and elements inside an enclosed space that resemble components of bridge structures to be inspected using UAVs, allowing repeatability of the test by controlling outside parameters such as lighting condition, wind, precipitation, temperature, and GPS signal. Using distances based on proximity effects, maximum typical rotor-tip-to-rotor-tip distance, and a gallery of bridges and situations when flying close to bridge structures, a final arrangement of elements is presented as the evaluation chamber. Components inside the evaluation chamber include both “real” steel and concrete specimens as well as those intended to simulate various geometric configurations on which other features are mounted. Pictures of damages of steel and concrete elements have been placed in the internal faces of the obstacles that can be assessed either in real-time flight or in post-processing work. A detailed comparison between the objectives of this research project and the results obtained by the evaluation chamber was performed using visual evaluation and resolution charts for the images obtained, the availability of visual line of sight during the test, and the absence of GPS signal.</p><p><br></p><p>From the comparison and analysis conducted and based on satisfactory flight results as images obtained during flights, the evaluation chamber is concluded to be a repeatable and reliable tool to apply to any UAS prior to inspect bridges and other structures, and the author recommends to refrain from conducting an inspection if the UAS does not comply with the minimum requirements presented in this research work. Additionally, this research provided a clearer understanding of the general phenomenon presented when UAVs approach structures and attempts to fill the gap of knowledge regarding minimum requirements and criterion for the use of UAS technologies in inspection of structures.</p>