Linghadharinee
A S
Biomedical Engineering · Neurotechnology · Biomedical Signals · AI
I like working where biology becomes data, and where data becomes something you can build. Right now that means EEG pipelines, motion signals and assistive devices.
Where the thing being measured is messy
I like problems where what you're trying to understand is untidy: a biological signal, a movement, a tremor, a motor task. The work is figuring out how engineering can make it measurable.
My path has moved from biomedical instrumentation and hardware, to physiological signals, to signal processing and machine learning, and now to EEG and neurotechnology. I enjoy moving between the physical side (sensors, boards, a glasses frame) and the computational side (filtering, features, models).
Research
IEEE EMBS RI-SO · Biomedical Sensors track
The problem
High-quality EEG systems can be expensive, hard to deploy, and concentrated in specialised clinical settings.
The direction
Our team is developing a lower-cost, more deployable EEG system to make early neurodevelopmental screening more accessible. We're guided by Anna Júlia Pereira Oliveira.
My role
I lead the EEG pipeline: signal processing, noise reduction, pipeline architecture and signal quality, so that captured EEG is useful for downstream analysis. The system is still in development and this is not a finished clinical pipeline.
- Raw EEG and signal acquisition
- Noise and artifact handling
- Preprocessing
- Signal quality assessment
- Feature and downstream analysis
- Possible clinical or research interpretation (future)