UTFacultiesEEMCSDisciplines & departmentsBSSEventsPARTLY DIGITAL (ONLY FOR INVITEES) : PhD Defence Mohamed Irfan Mohamed Refai | Moving On: Measuring Movement Remotely after Stroke

PARTLY DIGITAL (ONLY FOR INVITEES) : PhD Defence Mohamed Irfan Mohamed Refai | Moving On: Measuring Movement Remotely after Stroke

Moving On: Measuring Movement Remotely after Stroke

Due to the COVID-19 crisis the PhD defence of Mohamed Irfan Mohamed Refai will take place (partly) online.

The PhD defence can be followed by a live stream.

Mohamed Irfan Mohamed Refai is a PhD student in the research group Biomedical Signals and Systems (BSS). His supervisors are prof.dr.ir. P.H. Veltink and prof.dr. J.H. Buurke from the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS).

Most persons with stroke suffer from motor impairment, which restricts mobility on one side, and affects their independence in daily life activities. Measuring recovery is needed to develop individualized therapies. However, commonly used clinical outcomes suffer from low resolution and subjectivity. Therefore, objective biomechanical metrics should be identified to measure movement quality. However, non-portable laboratory setups are required in order to measure these metrics accurately. Alternatively, minimal wearable systems can be developed to simplify measurements performed at clinic or home to monitor recovery. Thus, the goal of the thesis was ‘To identify metrics that reflect movement quality of upper and lower extremities after stroke and develop wearable minimal systems for tracking the proposed metrics’.

Section Upper Extremity

First, we systematically reviewed literature (Chapter II) to identify metrics used to measure reaching recovery longitudinally post-stroke. Although several metrics were found, it was not clear how they differentiated recovery from compensation strategies. Future studies must address this gap in order to optimize stroke therapy. Next, we assessed a ‘valid’ measure for smoothness of upper paretic limb reaching (Chapter III), as this was commonly used to measure movement quality. After a systematic review and simulation analyses, we found that reaching smoothness is best measured using spectral arc length. The studies in this section offer us a better understanding of movement recovery in the upper extremity post-stroke.  

Section Lower Extremity

Although metrics that reflect gait recovery are yet to be identified, in this section we focused on developing minimal solutions to measure gait quality. First, we showed the feasibility of 1D pressure insoles as a light-weight alternative for measuring 3D Ground Reaction Forces (GRF) (Chapter IV). In the following chapters, we developed a minimal system; the Portable Gait Lab (PGL) using only three Inertial Measurement Units (IMUs) (one per foot and one on the pelvis). We explored the Centroidal Moment Pivot (CMP) point (Chapter V) as a biomechanical constraint that can help with the reduction in sensors. Then, we showed the feasibility of the PGL to track 3D GRF (Chapters VI – VII) and relative foot and CoM kinematics (Chapter VIII - IX) during variable over ground walking by healthy participants. Finally, we performed a limited validation study in persons with chronic stroke (Chapter X).  

This thesis offers knowledge and tools which can help clinicians and researchers understand movement quality and thereby develop individualized therapies post-stroke.