Virtual Reality and smart eyewear
Virtual reality opens new possibilities of research, also connected to the utilization of the inertial sensors inside the headset in order to detect, without using other wearables, cardiac and respiratory parameters. Current research is directed towards developing VR scenarios that could be utilized both in rehabilitation and prevention by exploiting real-time headset-embedded sensors in order to provide an immediate feedback to the user, to create an engagement and active experience capable to help reaching the proposed goals. In addition, as part of the Joint Research Project between Politecnico di Milano and Essilor Luxottica, we collaborate in the creation of the smartglasses of the future, by exploiting head-related biomarkers for lifestyle purposes.
Current research projects and collaborations
BMS Lab, University of Twente (NL)
Softcare Slr
Essilor-Luxottica
Relevant publications (updated Nov 25)
Mozzini F, Solbiati S, Bernasconi S, Angelucci A, Lo Mauro MA, Antonello N, Aliverti A, Trojaniello D, Caiani EG. Heart and breath dynamics: a preliminary study of cardiorespiratory coupling using smart-eyewear technology. Cinc 2025 (in press)
Scandelli A, Cenerini C, Crupi I, Mozzini F, Solbiati S, Caiani EG, Trojaniello D, Villa F. Comparative Waveform Analysis of Nasal and Finger PPG Signals for Non-Invasive Blood Pressure Estimation . Proc. Sensors Conf. 2025 (in press)
Solbiati S, Mozzini F, Sahler J, Gil P, Amir B, Antonello N, Trojaniello D, Caiani EG. Estimating heart rate from inertial sensors embedded in a smart-eyewear: a validation study. Sensors 2025;25(15):4531 https://doi.org/10.3390/s25154531
Carpi A, Solbiati S, Megale V, Caiani EG. An innovative web-based approach to generate respiratory biofeedback using virtual reality headset and embedded inertial sensors during an imposed breathing protocol: a proof-of-concept study. Biomedical Signal Processing and Control 2025;108:107966 https://doi.org/10.1016/j.bspc.2025.107966
Tauro E, Feliziani L, Manzo N, Van’t Klooster JW, Caiani EG. A Survey-Based Evaluation of Interactive Virtual Reality Scenarios to Assess Emotions. In: Singh D, van ’t Klooster JW, Tiwary US. (eds) Intelligent Human Computer Interaction. IHCI 2024. Lecture Notes in Computer Science, vol 15558. Springer, Cham 2025. https://doi.org/10.1007/978-3-031-88881-6_7
Tauro E, Feliziani L, Manzo N, Van ‘t Klooster J-W, Caiani EG. A Survey-based Evaluation of Interactive Virtual Reality Scenarios to Assess Emotions. Proc. IHCE 2024
Solbiati S, Charkas S, Mozzini F, Lo Mauro A, Bernasconi S, Angelucci A, Aliverti A, Caiani EG. Comparison of ECG-Free Algorithms for Heart Rate Computation From Head-BCG Signals Obtained With Smart Eyewear. Proc. IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering – IEEE MetroXRAINE 2024:213-218 10.1109/MetroXRAINE62247.2024.10795866
Solbiati S, Buffoli A, Megale V, Damato G, Lenzi B, Langfelder G, Caiani EG. Monitoring cardiac activity by detecting subtle head movements using MEMS technology, Proc. IEEE INERTIAL 2022:1-4
Solbiati S, Buffoli A, Megale V, Damato G, Lenzi B, Langfelder G, Caiani EG. Detecting heart rate from virtual reality headset-embedded inertial sensors: a kinetic energy approach. Proc. International Conference on e-Health and Bioengineering (EHB), 2021, pp. 1-4
Floris C, Solbiati S, Landreani F, Damato G, Lenzi B, Megale V, Caiani EG. Feasibility of heart rate and respiratory rate estimation by inertial sensors embedded in a virtual reality headset. Sensors 2020, 20, 7168