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Exploiting inertial sensing for human motion analysis and motor dynamics recognition
No full textLa crescente richiesta di monitoraggi continui, poco invasivi e a distanza del movimento umano sta orientando la biomeccanica verso l’uso di sensori indossabili, in particolare le unità di misura inerziali (IMU/MIMU). Sebbene i sistemi di motion capture da laboratorio restino il riferimento più accurato, costi elevati, complessità e volume di misura limitato ne impediscono l’uso prolungato e in contesti reali. I sensori inerziali rappresentano quindi un’alternativa promettente, pur introducendo sfide metodologiche come l’allineamento sensore–anatomia, la deriva del segnale e l’interpretazione dei dati in vita quotidiana, soprattutto in popolazioni con deficit motori.
In questo contesto, questa tesi approfondisce le basi metodologiche, le strategie computazionali e le applicazioni pratiche dei sistemi basati su MIMU per l’analisi del movimento umano, concentrandosi su tre aree: riconoscimento delle attività (HAR), stima della cinematica degli arti inferiori e valutazione della stabilità dinamica tramite il margine di stabilità (MoS). L’obiettivo è sviluppare soluzioni indossabili accurate, robuste e clinicamente utili per il monitoraggio quotidiano.
Il tema dell’HAR è stato investigato tramite due approcci: uno basato su algoritmi di machine learning “shallow” e uno su modelli di deep learning. Entrambi mostrano che una singola MIMU al polso può riconoscere gesti clinicamente rilevanti come bere o assumere una pillola. Configurazioni sensoriali essenziali hanno comunque prodotto elevata accuratezza. Caratteristiche ben ingegnerizzate hanno permesso ai modelli più semplici di raggiungere prestazioni comparabili a reti più complesse, mentre architetture ibride di deep learning hanno ulteriormente migliorato accuratezza e robustezza usando direttamente i segnali grezzi. È stato inoltre valutato il contributo informativo delle diverse tipologie di segnale.
La tesi analizza anche la stima della cinematica degli arti inferiori per la valutazione del cammino e la riabilitazione. È stato sviluppato un nuovo metodo di identificazione degli assi anatomici, basato su movimenti funzionali e minimizzazione ai minimi quadrati degli assi elicoidali istantanei, per allineare il frame del sensore a quello anatomico e ottenere stime articolari significative e clinicamente coerenti. È stata inoltre valutata la possibilità di ridurre i movimenti richiesti nella fase di calibrazione senza compromettere l’accuratezza nel piano sagittale, analizzando anche le stime nei piani frontale e trasverso. La validazione è stata estesa oltre il cammino lineare, includendo compiti funzionali come la svolta e il Timed Up and Go, confermando l’applicabilità della metodologia a movimenti complessi e reali.
Infine, la stabilità dinamica è stata esaminata tramite la stima del MoS utilizzando solo tre sensori inerziali. Un metodo completamente basato su MIMU per questa misura è ancora poco esplorato, e questo lavoro contribuisce a definirne la fattibilità come tecnica non invasiva per quantificare la stabilità dinamica, un indicatore cruciale del rischio di caduta, soprattutto negli anziani e nei soggetti fragili. Sebbene preliminari, i risultati mostrano un buon accordo tra misure inerziali e marker-based sia in soggetti sani sia in persone con Parkinson, evidenziando il potenziale dell’approccio e il ruolo diagnostico dei compiti di svolta.
Nel complesso, questi contributi gettano le basi per tecnologie indossabili di nuova generazione a supporto della diagnosi precoce, della riabilitazione personalizzata e del monitoraggio a lungo termine della funzione motoria in contesti reali.The increasing demand for continuous, unobtrusive, and remote monitoring of human movement is shifting biomechanics toward wearable sensors, particularly inertial measurement units (IMUs/MIMUs). While laboratory-based motion capture remains the gold standard, its cost, complexity, and limited acquisition volume prevent long-term and real-world use. Wearable inertial sensors offer a valid alternative, enabling prolonged monitoring with minimal intrusion, but they introduce methodological challenges such as sensor–anatomy alignment, signal drift, and context interpretation, especially in populations with motor impairments.
In this context, this thesis investigates the methodological foundations, computational strategies, and practical applications of MIMU-based systems for human motion analysis, focusing on three areas: human activity recognition (HAR), lower-limb joint kinematics, and dynamic stability assessment through the margin of stability (MoS). The aim is to develop accurate, robust, and clinically meaningful wearable solutions for everyday monitoring.
Inertial-based HAR has been addressed through two frameworks: one using shallow machine-learning classifiers and another relying on deep-learning models. Both approaches show that a single wrist-mounted MIMU can reliably recognize clinically relevant upper-limb gestures, such as drinking or pill intake. High classification accuracy was achieved even with minimal sensor configurations. Carefully engineered features enabled machine-learning models to match more complex networks, while hybrid deep-learning architectures further improved accuracy and robustness using raw inertial data. The contribution of individual signals and their combinations was also examined.
The thesis also explores lower-limb kinematic estimation for gait analysis and rehabilitation. A new anatomical axis identification method was developed, using functional movements and least-squares minimization of instantaneous helical axes to align sensor and anatomical frames. This enabled meaningful and clinically compliant joint angle estimation. The study also assessed whether calibration movements could be reduced without compromising sagittal-plane accuracy, while also evaluating performance in the frontal and transverse planes. Validation extended beyond straight-line gait to include clinically relevant tasks such as turning and the Timed Up and Go, demonstrating the method’s applicability to complex, real-world movements.
Dynamic stability was further investigated through MoS estimation using only three inertial sensors. Fully MIMU-based MoS computation is still largely unexplored, and this work contributes to establishing it as a feasible, unobtrusive technique for quantifying dynamic stability—a key predictor of fall risk, especially in older or frail individuals. Although preliminary, the results show good agreement between inertial- and marker-based measures in both healthy and Parkinson’s disease participants, highlighting the potential of this approach and the diagnostic importance of turning tasks.
Overall, these contributions support the development of next-generation wearable technologies for early diagnosis, personalized rehabilitation, and long-term monitoring of motor function in real-world environments
Inertial Sensing for Human Motion Analysis: Enabling Sensor-to-Body Calibration Through an Anatomical and Functional Combined Approach
No full textThe use of inertial measurement units is gaining attention to estimate human joint kinematics. However, to obtain clinically meaningful results, sensor frame needs to be aligned with the underlying anatomical one. Although during the years different approaches have been proposed, a common consensus has not been reached. Further, inertial sensor positioning on human segments can affect frame definition and kinematics estimation. Thus, the aim of the present work is to define an anatomical calibration procedure for lower limb joints kinematics, robust with respect to sensor misalignment, and based on a limited set of movements, with static and functional assumptions. To this purpose, straight walking and turning motor tasks in six healthy subjects were considered, and results were compared with those provided by an optoelectronic system. Three sensor placements have been also evaluated to test the procedure with respect to sensor positioning. After offset removal, an average RMSE ≤2.5 deg in gait, and ≤2 deg in turning for all the configurations were obtained, outperforming results from previous approaches. Average offset values resulted about 6 deg for hip and ankle, whereas negligible for the knee. Outcomes of this study enable a simple and accurate measurement of clinically meaningful joints kinematics, also without a strict sensor placement
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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