Bioengineering of exercise: biomechanical and metabolic aspects

The field of research of this dissertation concerns the bioengineering of exercise, in particular the relationship between biomechanical and metabolic knowledge. This relationship can allow to evaluate exercise in many different circumstances: optimizing athlete performance, understanding and helping compensation in prosthetic patients and prescribing exercise with high caloric consumption and minimal joint loading to obese subjects. Furthermore, it can have technical application in fitness and rehabilitation machine design, predicting energy consumption and joint loads for the subjects who will use the machine. The aim of this dissertation was to further understand how mechanical work and metabolic energy cost are related during movement using interpretative models. Musculoskeletal models, when including muscle energy expenditure description, can be useful to address this issue, allowing to evaluate human movement in terms of both mechanical and metabolic energy expenditure. A whole body muscle-skeletal model that could describe both biomechanical and metabolic aspects during movement was identified in literature and then was applied and validated using an EMG-driven approach. The advantage of using EMG driven approach was to avoid the use of arbitrary defined optimization functions to solve the indeterminate problem of muscle activations. A sensitivity analysis was conducted in order to know how much changes in model parameters could affect model outputs: the results showed that changing parameters in between physiological ranges did not influence model outputs largely. In order to evaluate its predicting capacity, the musculoskeletal model was applied to experimental data: first the model was applied in a simple exercise (unilateral leg press exercise) and then in a more complete exercise (elliptical exercise). In these studies, energy consumption predicted by the model resulted to be close to energy consumption estimated by indirect calorimetry for different intensity levels at low frequencies of movement. The use of muscle skeletal models for predicting energy consumption resulted to be promising and the use of EMG driven approach permitted to avoid the introduction of optimization functions. Even though many aspects of this approach have still to be investigated and these results are preliminary, the conclusions of this dissertation suggest that musculoskeletal modelling can be a useful tool for addressing issues about efficiency of movement in healthy and pathologic subjects.

Ottimizzazione del consumo dei grassi durante esercizio fisico: studio di un test per il target mirato di allenamento individuale

Il primo studio ha verificato l'affidabilità del software Polimedicus e gli effetti indotti d'allenamento arobico all’intensità del FatMax. 16 soggetti sovrappeso, di circa 40-55anni, sono stati arruolati e sottoposti a un test incrementale fino a raggiungere un RER di 0,95, e da quel momento il carico è stato aumentato di 1 km/ h ogni minuto fino a esaurimento. Successivamente, è stato verificato se i valori estrapolati dal programma erano quelli che si possono verificare durante a un test a carico costante di 1ora. I soggetti dopo 8 settimane di allenamento hanno fatto un altro test incrementale. Il dati hanno mostrato che Polimedicus non è molto affidabile, soprattutto l'HR. Nel secondo studio è stato sviluppato un nuovo programma, Inca, ed i risultati sono stati confrontati con i dati ottenuti dal primo studio con Polimedicus. I risultati finali hanno mostrato che Inca è più affidabile. Nel terzo studio, abbiamo voluto verificare l'esattezza del calcolo del FatMax con Inca e il test FATmaxwork. 25 soggetti in sovrappeso, tra 40-55 anni, sono stati arruolati e sottoposti al FATmaxwork test. Successivamente, è stato verificato se i valori estrapolati da INCA erano quelli che possono verificarsi durante un carico di prova costante di un'ora. L'analisi ha mostrato una precisione del calcolo della FatMax durante il carico di lavoro. Conclusione: E’ emersa una certa difficoltà nel determinare questo parametro, sia per la variabilità inter-individuale che intra-individuale. In futuro bisognerà migliorare INCA per ottenere protocolli di allenamento ancora più validi.

Integrating the age factor in designing industrial environments and workstations in the workforce ageing era

As people spend a third of their lives at work and, in most cases, indoors, the work environment assumes crucial importance. The continuous and dynamic interaction between people and the working environment surrounding them produces physiological and psychological effects on operators. Recognizing the substantial impact of comfort and well-being on employee satisfaction and job performance, the literature underscores the need for industries to implement indoor environment control strategies to ensure long-term success and profitability. However, managing physical risks (i.e., ergonomic and microclimate) in industrial environments is often constrained by production and energy requirements. In the food processing industry, for example, the safety of perishable products dictates storage temperatures that do not allow for operator comfort. Conversely, warehouses dedicated to non-perishable products often lack cooling systems to limit energy expenditure, reaching high temperatures in the summer period. Moreover, exceptional events, like the COVID-19 pandemic, introduce new constraints, with recommendations impacting thermal stress and respiratory health. Furthermore, the thesis highlights how workers' variables, particularly the aging process, reduce tolerance to environmental stresses. Consequently, prolonged exposure to environmental stress conditions at work results in cardiovascular disease and musculoskeletal disorders. In response to the global trend of an aging workforce, the thesis bridges a literature gap by proposing methods and models that integrate the age factor into comfort assessment. It aims to present technical and technological solutions to mitigate microclimate risks in industrial environments, ultimately seeking innovative ways to enhance the aging workforce's comfort, performance, experience, and skills. The research outlines a logical-conceptual scheme with three main areas of focus: analyzing factors influencing the work environment, recognizing constraints to worker comfort, and designing solutions. The results significantly contribute to science by laying the foundation for new research in worker health and safety in an ageing working population's extremely current industrial context.