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Defence of doctoral thesis in the field of Micro- and Nanoelectronic Circuit Design, M.Sc.(Tech.) Olaitan Olabode

The title of the thesis is Integrated Time-based Sensor Interface Circuits for Implant Applications
Picture of one of the fabricated chips in a QFN-48 package.

M.Sc.(Tech.) Olaitan Olabode will defend the thesis "Integrated Time-based Sensor Interface Circuits for Implant Applications" on 26 November 2021 at 12 in Aalto University School of Electrical Engineering, Department of Electronics and Nanoengineering, in lecture hall AS1, Maarintie 8, Espoo, and online in Zoom.

Opponent: Prof. Tor Sverre Lande, University of Oslo, Norway
Custos: Prof. Jussi Ryynänen, Aalto University School of Electrical Engineering, Department of Electronics and Nanoengineering

The public defense will be organized via remote technology. Follow defence: https://aalto.zoom.us/j/64404193256
Zoom Quick Guide: https://www.aalto.fi/en/services/zoom-quick-guide

Thesis available for public display at: https://aaltodoc.aalto.fi/doc_public/eonly/riiputus/

Doctoral theses in the School of Electrical Engineering: https://aaltodoc.aalto.fi/handle/123456789/53

Press release:

The prevalence of neurodegenerative diseases such as Parkinson’s, Alzheimer’s, dementia, epilepsy, and schizophrenia, is expected to increase with the aging population. Consequently, there is a growing need to further study the nature of these diseases in order to develop improved medical diagnostics for early detection and treatments.

This work focuses on the design of integrated time-based sensor interfaces for implant applications in order to facilitate remote health monitoring and care, which has become important in view of the global pandemic. However, the design of integrated sensor interfaces for biomedical and implant applications is challenging because of limited resources in terms of energy and area.

The proposed circuits in this work leverage on the advances in semiconductor technology that favours time-based processing, low supply voltages, and small area designs. As a result, time-based analog-to-digital conversion techniques are explored in the design of the proposed sensor interface circuits, targeted towards monitoring of neurochemical and biopotential signals. Measured results from the time-based sensor interface circuit for neurochemical sensing demonstrate the detection of physiologically-relevant dopamine concentration, which is beneficial for adjusting stimulation parameters in patients fitted with deep brain stimulators for treating neurological, psychological, and behavioural disorders, including addiction and depression.

Furthermore, the presented circuits in this dissertation can be utilized in implantable and biomedical sensor applications for achieving moderate to high resolution, scalable, energy, area, and cost-efficient solutions in for example, the design of pacemakers, glucose monitors, cochlear implants, and wearable devices for real-time monitoring of vital signs.

Contact information of the doctoral candidate:

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