Marco Alban-Paccha

Research

Work spans three layers that meet in the clinic.

Devices and materials

OECT biosensors, biopotential interfaces and soft microfluidics for sweat and interstitial fluid sensing.

Embedded systems

Low-power analogue front ends, BLE connectivity and mobile apps for robust field capture.

Algorithms and AI

Signal processing, sensor fusion and clinically informed ML for health assessment and decision support.

Projects

ADVANTAGE project

ADVANTAGE: Visceral Pain Research

This consortium project targets the neural mechanisms of visceral pain, developing wearable and implantable bioelectronic sensors to monitor and treat complex conditions. Collaborating across Cambridge’s Medicine & Engineering departments, we integrate low‑power electronics and targeted interventions to personalize chronic pain management.

Cardiovascular Monitoring

Cardiovascular Monitoring

A dry‑electrode wearable platform capturing ECG and PPG to estimate blood pressure cufflessly. Comfortable chest adhesion, smartphone‑linked AI analytics, and seamless data streaming make continuous cardiac monitoring accessible for clinical trials and patient care.

Multimodal Electrochemical Sensing

Multimodal Electrochemical Sensing

An OECT‑based wearable that non‑invasively measures glucose, lactate, and electrolytes in sweat via microfluidics. Real‑time, low‑power data is wirelessly streamed for metabolic health, diabetes management, and athletic performance optimization.

Selected publications

  1. Tao, X., Carnicer Lombarte, A., Dominguez Alfaro, A., Gatecliff, L., Zhang, J., Bidinger, S., Keene, S.T., Naegele, T.E., El Hadwe, S., Dong, C., Boys, A.J., Slaughter, C., Ruiz-Mateos Serrano, R., Alban-Paccha, M.V., Kar-Narayan, S., and Malliaras, G.G. (2025). Cleanroom-Free Toolkit for Integrating Submicron-Resolution Bioelectronics on Flexibles. Small, https://doi.org/10.1002/smll.202411979
  2. Serrano, R. R-M., Aguzin, A., Mitoudi-Vagourdi, E., Tao, X., Naegele, T., Jin, A., Lopez-Larrea, N., Picchio, M.L., Alban-Paccha, M.V., Minari, R.J., Mecerreyes, D., Dominguez-Alfaro, A., and Malliaras, G.G. (2024). 3D Printed PEDOT:PSS-based Conducting and Patternable Eutectogel Electrodes for Machine Learning on Textiles. Biomaterials, https://doi.org/10.1016/j.biomaterials.2024.122624
  3. Alban, M.V., Lee, H., Moon, H., and Yoo, S. (2021). Micromolding Fabrication of Biocompatible Dry Micro-Pyramid Array Electrodes for Wearable Biopotential Monitoring. IOP Flexible and Printed Electronics, https://doi.org/10.1088/2058-8585/ac3561
  4. Lee, H., Lee, W., Lee, H., Kim, S., Alban, M.V., Song, J., Kim, T., Lee, S., and Yoo, S. (2021). Organic–Inorganic Hybrid Approach to Pulse Oximetry Sensors with Reliability and Low Power Consumption. ACS Photonics, https://doi.org/10.1021/acsphotonics.1c01161

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