Biomedical Engineering
The Biomedical Engineering Research Area brings together four research groups within the Department: InVisioning Lab, DHI – Digital Healthcare Innovation, H-Move Group, and LISiN. The activities of the area are mainly focused on the development of methods, technologies, and devices for the acquisition, processing, and interpretation of biomedical data, with the aim of providing tools for prevention, diagnosis, monitoring, treatment, and rehabilitation.
The expertise within the area covers several fields of biomedical engineering, ranging from the development of biomedical instrumentation and medical software to the analysis of biological signals and biomedical images, from mathematical modelling to digital healthcare. These skills are integrated within a shared approach oriented towards the quantitative study of biological phenomena at different scales, from tissue microstructure to the motor, cognitive, and behavioural functions of the individual.
A distinctive feature of the area is the development of biomedical instrumentation. The activities include the design, prototyping, and validation of medical electrical devices, with particular attention to equipment for biopotential recording, sensors for the monitoring of physiological variables, wearable technologies, and telemonitoring solutions.
Starting from the acquired data, the area develops advanced methods for the analysis of biomedical images and signals, integrated with artificial intelligence techniques. Activities include, among others, the extraction of quantitative descriptors from histological images, ultrasound data, photoacoustic imaging, electrophysiological signals, kinematic and dynamic measurements, and multimodal data. Particular attention is devoted to the robustness, verifiability, and interpretability of the algorithms, which are fundamental aspects to ensure that the obtained results can be reliably used in biomedical contexts.
The same methodological approach is adopted in the development of digital solutions for medicine and for the organization of healthcare processes. In this context, the area conducts research activities on clinical decision-support systems, tools for the management and analysis of heterogeneous clinical data, digital twins of biological systems, and technologies for remote monitoring. These activities aim to improve diagnostic effectiveness, the personalization of interventions, and support more continuous and distributed models of care.
The study of neuromuscular function in physiological and pathological conditions represents a cross-cutting activity in which several of the previously described activities converge and are integrated. Advanced electrophysiological techniques, muscle imaging, and kinematic and dynamic measurements allow increasing our understanding of the central and peripheral mechanisms of the neuromuscular system in physiological and pathological conditions, and to assess the effects of ageing, disuse, training, rehabilitation or pharmacological treatments, stress, and cognitive load. Applications include, among others, motor rehabilitation, ergonomics, sport, and occupational medicine.
Overall, the Biomedical Engineering Research Area has a strong experimental and translational profile. Methodological and technological development is complemented by prototyping, experimental validation, and transfer activities towards clinical, industrial, and sports-related contexts. In this sense, the area aims to contribute to the development of more quantitative and personalised medicine by providing tools that can transform complex data into information usable by researchers, clinicians, healthcare professionals, and end users.
The expertise within the area covers several fields of biomedical engineering, ranging from the development of biomedical instrumentation and medical software to the analysis of biological signals and biomedical images, from mathematical modelling to digital healthcare. These skills are integrated within a shared approach oriented towards the quantitative study of biological phenomena at different scales, from tissue microstructure to the motor, cognitive, and behavioural functions of the individual.
A distinctive feature of the area is the development of biomedical instrumentation. The activities include the design, prototyping, and validation of medical electrical devices, with particular attention to equipment for biopotential recording, sensors for the monitoring of physiological variables, wearable technologies, and telemonitoring solutions.
Starting from the acquired data, the area develops advanced methods for the analysis of biomedical images and signals, integrated with artificial intelligence techniques. Activities include, among others, the extraction of quantitative descriptors from histological images, ultrasound data, photoacoustic imaging, electrophysiological signals, kinematic and dynamic measurements, and multimodal data. Particular attention is devoted to the robustness, verifiability, and interpretability of the algorithms, which are fundamental aspects to ensure that the obtained results can be reliably used in biomedical contexts.
The same methodological approach is adopted in the development of digital solutions for medicine and for the organization of healthcare processes. In this context, the area conducts research activities on clinical decision-support systems, tools for the management and analysis of heterogeneous clinical data, digital twins of biological systems, and technologies for remote monitoring. These activities aim to improve diagnostic effectiveness, the personalization of interventions, and support more continuous and distributed models of care.
The study of neuromuscular function in physiological and pathological conditions represents a cross-cutting activity in which several of the previously described activities converge and are integrated. Advanced electrophysiological techniques, muscle imaging, and kinematic and dynamic measurements allow increasing our understanding of the central and peripheral mechanisms of the neuromuscular system in physiological and pathological conditions, and to assess the effects of ageing, disuse, training, rehabilitation or pharmacological treatments, stress, and cognitive load. Applications include, among others, motor rehabilitation, ergonomics, sport, and occupational medicine.
Overall, the Biomedical Engineering Research Area has a strong experimental and translational profile. Methodological and technological development is complemented by prototyping, experimental validation, and transfer activities towards clinical, industrial, and sports-related contexts. In this sense, the area aims to contribute to the development of more quantitative and personalised medicine by providing tools that can transform complex data into information usable by researchers, clinicians, healthcare professionals, and end users.