Jose Maria
Perez-Macias

Bio

check My NOW page

I lead complex, multidisciplinary technical projects.

As a Technical Lead and systems engineer, I specialize in directing deep-tech hardware, embedded firmware, and biomedical algorithms from initial concept to validated product. My leadership spans the ARPA-H Research to Business (R2B) initiative at Aalto University, representing Emfit Oy as technical delegate in European Union consortia, prototyping next-generation wearables at Huawei Concept Lab Helsinki, conducting clinical signal processing at Tampere University Hospital (TAYS), and contributing to the EU FP7 program at Philips Research.

With degrees in telecommunications and a PhD in biomedical engineering from Tampere University, I bridge the gap between sensor hardware, machine learning algorithms, clinical validation, and business translation. I am currently focusing on leading technical projects as Technical Lead in healthtech, physiological sensors, wearables, or AI-driven medical devices.

For a more detailed CV, ask me for my CV in PDF. My ORCID: 0000-0003-3485-0874

Technical Leadership & Industry Track Record

• Technical Lead — ARPA-H Research to Business (R2B) Project: Directing end-to-end technical execution across sensor architecture, embedded firmware, custom electronics, biomedical algorithms, and system verification & validation (V&V) testing at Aalto University.
• Health Scientist — Emfit Ltd (Emfit Oy): Represented the company as Health Scientist in two European Union consortia; led algorithm design and validation for unobtrusive sleep monitoring and acoustic snoring detection.
• Wearables R&D Researcher — Huawei Helsinki Concept Lab: Led biosignal evaluation (PPG, EMG, ECG), prototype hardware testing, and motion-artifact cancellation algorithms for smartwatch platforms.
• Clinical Systems Lead — Tampere University Hospital (TAYS): Spearheaded clinical data acquisition protocols, ICU continuous EEG monitoring algorithms, and sleep laboratory polysomnography (PSG) sensor calibrations.
• Consortium Contributor — Philips Research Laboratories (Aachen, Germany): Contributed to the European Commission FP7 “MyHeart” consortium on wearable cardiovascular monitoring systems.

I defended my thesis in June 2025 at Tampere University, Finland, specializing in sleep monitoring and signal processing. Read the Tampere University research announcement. I was also featured in the national press: read the feature news article.

Outside research, I play piano and explore how music and technology intersect, often inspiring my signal processing projects. As a strange quirk... I do enjoy reading patents.

Research

The topic of my doctoral thesis is centered on sleep, unobtrusive sensors and mattress sensors (such as Beddit, Emfit (electromechanical film transducer) mattress , Fitbit, Firstbeat, raw accelerometers like traxmeet). The thesis proposes several state-of-the-art methods for detecting snoring, breathing efforts, breathing patterns, and heart rate detection algorithms.

Research Lines

• Wrist EMG for Smartwatch PPG Heart Rate Accuracy (IEEE Sensors Journal 2022)
• Snoring detection in Emfit mattress sensor
• Breathing disorders - Breathing efforts using Emfit mattress sensor
• Heart beat detection in Emfit mattress sensor
• Breathing detection using video and other signals
• Intensive Care Unit (ICU) EEG trends I wrote software to analyze EEG trends in intensive care patients, an ongoing project I was supporting (2021) - When the time comes I share the Git Project.

Community projects

• locally-informed, this is the only community project I have participated back in 2020. Updating information from Finland.

Audio / Sound Projects

• Spatial Sound & Sound Synthesis using Csound: A project on 3D spatial sound and acoustic wave synthesis from a course on "Sound and Wave Engineering" back in 2003/2004 (Universidad de Valladolid) with classmate Ariana, inspired by Richard Boulanger's Csound work. We documented spatial audio opcodes, HRTF models, and created custom examples. You can browse the modernized documentation in English, in Spanish, or explore the preserved original 2004 historical archive (Universidad de Valladolid, LPI-UVa).
• Acoustic Source Localization & Vehicle Tracking: Educational project from the Advanced Audio Processing course at Tampere University (supervised by Pasi Pertilä). Explores how an 8-channel circular microphone array (miniDSP UMA-8) and Steered Response Power with Phase Transform (SRP-PHAT) beamforming algorithms passively localize and track moving vehicles in road traffic. Read the educational project tutorial or view the source code on GitHub.

Resources