Lucian Bezuidenhout

Lucian Bezuidenhout

Assistant Professor
Visiting address: Alfred Nobels Allé 23, 14183 Huddinge
Postal address: H1 Neurobiologi, vårdvetenskap och samhälle, H1 Fysioterapi Franzen, 171 77 Stockholm

About me

  • I am a Physics PhD graduate with a vast variety of research interests
    comprising renewable energy, seismology, physical activity and neuroimaging.
    Overall, I have worked in various laboratories and conducted a broad range of
    experiments in a transdisciplinary environment. In my current role at the
    Division of Physiotherapy at Karolinska Institute, I manage data obtained
    from activity monitors and develop various automated algorithms for analysis
    of raw physical activity data. Additionally, I develop protocols for
    assessment of cortical brain activity using functional near-infrared
    spectroscopy. I am proficient in various programming software’s and skilled
    in digital signal processing.
    2019: ICE Telford Premium
    Prize publishing award
    2011
  • 2014-2017: National Research Foundation (Innovation) Grant.
    2011-2017: Nelson Mandela University post
    graduate Grant.
    2012-2013: Centre for Energy Research Grant.
    2013: Erasmus Mundus
    Action to Europe Scholarship.
    2018 PhD (Physics) – Thesis Title: Using ambient noise tomography to
    image the Eastern Cape-Karoo and Karoo regions, South Africa. Nelson Mandela
    University.
    2013 MSc (Physics) – Thesis Title: On the characterization of
    photovoltaic device parameters using light beam induced current measurement.
    Nelson Mandela University.
    2011 BScHons (Physics). Nelson Mandela University.
    2010 BSc (Applied Mathematics and Physics). Nelson Mandela University.

Research

  • My research focuses include understanding physical activity behavior in
    people with neurological diseases by analyzing data obtained from activity
    monitors. Additionally, I am investigating the feasibility of using
    functional near-infrared spectroscopy (fNIRS) - a non-invasive brain imaging
    method, in different healthy populations across the life-span and clinical
    populations (e.g. Parkinson’s disease (PD), Multiple sclerosis (MS) and
    stroke) with mobility impairments. I am also developing and testing a new
    conceptual framework to portray physical activity which integrates objective
    assessed physical activity using accelerometry, with the contextual setting
    where the activity is performed using global positioning systems (GPS) and
    environmental layers (e.g. google earth).

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