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Sensors and Embedded Systems Design Lab (EMsensED Lab)

Team members


The research activity of EMsensED Lab is focused on the design of embedded systems based on Microcontrollers and/or FPGAs. The research group gained relevant experience in the implementation of advanced algorithms for data elaboration, and in the design of wearable/portable IoT sensors based on Wi-Fi, ZigBee and NB-IoT protocols, and of analog circuits for sensor interface, signal amplification, and analog-to-digital signal conversion.

The actual research interests are summarized in the following:

  • Design of wearable sensors for human activity monitoring (in sports, in everyday life ...);
  • Development of portable IoT sensors, based on the Wi-Fi technology, dedicated to electrochemical analysis for Point-of-Care Testing (POCT);
  • Design of FPGA systems for the sensing of State of Charge (SOC) /State of Health (SOH) of battery cells;
  • Design of arithmetic blocs for digital processing on FPGA.


Contact person: Ilaria De Munari – ilaria.demunari@unipr.it

Recent Research Projects
  • Participation to the Project ``Biosensoristica innovativa per i test sierologici e molecolari e nuovi dispositivi PoCT per la diagnosi di infezione da SARS-CoV-2'' funded in 2020, by ``Bando Straordinario di Ateneo per Progetti di Ricerca Biomedica in Ambito SARS-COV-2 e COVID-19,'' University of Parma.
  • Project “Advanced Approaches for batteries State of Charge (SoC) evaluation”, funded in 2021 by Programme “FIL-Quota Incentivante” of University of Parma and co-sponsored by Fondazione Cariparma (project leader: Valentina Bianchi)
Selected publications
  1. Stighezza, M., Bianchi, V., De Munari, I., “FPGA Implementation of an Ant Colony Optimization Based SVM Algorithm for State of Charge Estimation in Li-Ion Batteries”, (2021) Energies, 14 (21), art. no. 7064.
  2. Bianchi, V., Boni, A., Bassoli, M., Giannetto, M., Fortunati, S., Careri, M., De Munari, I., “IoT and Biosensors: A Smart Portable Potentiostat with Advanced Cloud-Enabled Features”, (2021) IEEE Access, 9, pp. 141544-141554.
  3. Boni, A., Bianchi, V., Ricci, A., De Munari, I., “NB-IoT and Wi-Fi Technologies: An Integrated Approach to Enhance Portability of Smart Sensors”, (2021) IEEE Access, 9, art. no. 9435286, pp. 74589-74599.
  4. Stighezza, M., Bianchi, V., De Munari, I., “HDL Code Generation from SIMULINK Environment for Li-Ion Cells State of Charge and Parameter Estimation”, (2021) Lecture Notes in Electrical Engineering, 738, pp. 136-143.
  5. Bianchi, V., De Munari, I., “A modular Vedic multiplier architecture for model-based design and deployment on FPGA platforms”, (2020) Microprocessors and Microsystems, 76, art. no. 103106.
  6. Bianchi, V., Boni, A., Fortunati, S., Giannetto, M., Careri, M., De Munari, I., “A Wi-Fi Cloud-Based Portable Potentiostat for Electrochemical Biosensors”, (2020) IEEE Transactions on Instrumentation and Measurement, 69 (6), art. no. 8762122, pp. 3232-3240.
  7. Bianchi, V., Mattarozzi, M., Giannetto, M., Boni, A., De Munari, I., Careri, M., “A self-calibrating iot portable electrochemical immunosensor for serum human epididymis protein 4 as a tumor biomarker for ovarian cancer”, (2020) Sensors (Switzerland), 20 (7), art. no. 2016.
  8. Bassoli, M., Bianchi, V., De Munari, I., “A model‐based design floating‐point accumulator. Case of study: FPGA implementation of a support vector machine kernel function”, (2020) Sensors (Switzerland), 20 (5), art. no. 1362.
  9. Bianchi, V., Savi, F., De Munari, I., Barater, D., Buticchi, G., Franceschini, G., “Minimization of network induced jitter impact on FPGA-based control systems for power electronics through forward error correction”, (2020) Electronics (Switzerland), 9 (2), art. no. 281.
  10. Bassoli, M., Bianchi, V., De Munari, I., “A Simulink Model-Based Design of a Floating-Point Pipelined Accumulator with HDL Coder Compatibility for FPGA Implementation”, (2020) Lecture Notes in Electrical Engineering, 627, pp. 163-171.
  11. Bianchi, V., Bassoli, M., De Munari, I., “Comparison of FPGA and microcontroller implementations of an innovative method for error magnitude evaluation in reed–solomon codes”, (2020) Electronics (Switzerland), 9 (1), art. no. 89.
  12. Bianchi, V., Bassoli, M., Lombardo, G., Fornacciari, P., Mordonini, M., De Munari, I., “IoT Wearable Sensor and Deep Learning: An Integrated Approach for Personalized Human Activity Recognition in a Smart Home Environment”, (2019) IEEE Internet of Things Journal, 6 (5), art. no. 8727452, pp. 8553-8562.
  13. Bianchi, V., Ciampolini, P., De Munari, I., “RSSI-Based Indoor Localization and Identification for ZigBee Wireless Sensor Networks in Smart Homes”, (2019) IEEE Transactions on Instrumentation and Measurement, 68 (2), art. no. 8412766, pp. 566-575.
  14. Giannetto, M., Bianchi, V., Gentili, S., Fortunati, S., De Munari, I., Careri, M., “An integrated IoT-Wi-Fi board for remote data acquisition and sharing from innovative immunosensors. Case of study: Diagnosis of celiac disease”,  (2018) Sensors and Actuators B: Chemical, 273, pp. 1395-1403.
  15. Bassoli, M., Bianchi, V., De Munari, I., “A plug and play IoT Wi-Fi smart home system for human monitoring”, (2018) Electronics (Switzerland), 7 (9), art. no. 200.
  16. Bassoli, M., Bianchi, V., De Munari, I., Ciampolini, P., “An IoT approach for an AAL Wi-Fi-based monitoring system”, (2017) IEEE Transactions on Instrumentation and Measurement, 66 (12), art. no. 8057592, pp. 3200-3209.
Pubblicato Martedì, 22 Marzo, 2022 - 09:14 | ultima modifica Martedì, 22 Marzo, 2022 - 10:15