Student Projects

Automatische Vervollständigung von Markertrajektorien

Oft wird der menschliche Gang mit passiven Bewegungserfassungssystemen untersucht, bei denen mithilfe von Infrarotkameras die Positionen von reflektiven Markern auf der Körperoberfläche ermittelt werden. So können die Trajektorien der Gliedmaßen gemessen werden und für biomechanische Analysen sowie muskuloskeletale Modelle benutzt werden. Nach der Messung im Bewegungslabor müssen die Daten ausgewertet werden, was die Zuordnung der Marker zu den Gliedmaßen („labeling“) und die Vervollständigung und Filterung ihrer Trajektorien beinhaltet. Im Allgemeinen wird ein Markermodell an die Daten gefittet, sodass die Zuordnung vieler Marker automatisch erkannt wird. Dennoch werden oft Marker falsch zugeordnet oder weisen Lücken in ihren Trajektorien auf, was bisher manuell ausgebessert werden muss. Es wurden jedoch schon fortschrittlichere Algorithmen für die Identifikation von Markern und auch eine kürzlich veröffentlichte Methode zur Vervollständigung der Trajektorien mithilfe inverser Kinematik entwickelt. Das Ziel dieser praktischen Arbeit ist die Trajektorienvervollständigung zu automatisieren sowie die Implementierung und Validierung der Open-Source Bibliothek der benutzten Inverse-Kinematik Methode. Weiterhin könnten auch andere Algorithmen zur automatischen Identifikation der Marker implementiert und getestet werden.

(potentielle) Aufgaben:

  • Suche nach Methoden für automatische Trajektorienvervollständigung und Identifikation von Markern
  • Programmieren in Matlab: Implementierung dieser Methoden in die Standard-Auswertungspipelines des Labors

Betreuerin: Dr. Lizeth Sloot


Instrumented Chair and Dual Tasking: new insights into unstable Sit-to-Stance

Even though many falls in older adults occur during sit-to-stand transitions, few studies have analyzed the mechanics of standing up from – let alone sitting down on – a chair. In addition, many studies evaluated artificially controlled movements: with arms crossed on the chest, without arm rests and while participants perform as good as they can at their own pace under the watchful eye of the researcher or clinician. In the ORB group we developed an instrumented chair to measure movement (motion capture), foot forces (force plates), electromyography simultaneous with the forces exerted at chair handles and seating. This allows for a deeper understanding of how young and older adults move while standing up and how dependent they are on support such as handles. In addition, we aim to set up a study to evaluate how sit-to-stand is affected by different tasks to challenge or distract participants while getting up or sitting down, including dual tasks, late cueing, and challenging surfaces. These conditions might expose more subtle impairments in older adults and thus important to include in (clinical) tests.

(potential) Tasks:

  • Connect, synchronize, and calibrate the force sensors of the instrumented chair
  • Biomechanics measurements (motion capture, forces, EMG) of sit-to-stand and stand-to-sit
  • Modeling: e.g. add arm rests to human model, optimization of movement
  • Develop, test and evaluate dual-tasking protocol

Supervisors: Dr. Lizeth Sloot & Dr. Matt Millard


Robotic Rollator and Instrumented Handles: assisted movement in elderly

Even though a considerable number of older adults depend on a rollator to get around, few studies have evaluated the interaction between older adults and rollators. Some studies evaluated high-level outcome parameters during steady-state walking with a rollator at preferred speed, but evaluation of other important daily tasks are lacking, such as sit-to-stance transfers, gait initiation, turning, and walking at different walking speeds, with and without dual task.

With the introduction of robotic rollators on the consumer market, new opportunities arise to actively support older adults and target specific movement impairments. To increase the knowledge necessary to design biologically inspired control of assistance during different task, we instrumented the handles of a conventional rollator, bought a commercially available robotic rollator to test and developed a robotic-rollator simulator testbed. We aim to 1) capture baseline movement during daily movements in older adults such as turning and with dual-task distraction; 2) compare movement without support to with an instrumented robotic rollator and/or a conventional rollator; and 3) design and evaluate active, targeted assistance of different task with the rollator simulator.

(potential) Tasks:

  • Connect, synchronize, and calibrate force sensing handles of the conventional rollator
  • Biomechanics measurement (potential: motion capture, forces / pressure insoles, EMG) of movement without, with conventional (with instrumented handles) and robotic rollator in young and older adults. This can focus on different tasks: sit-to-stance and stance-to-sit, gait (initiation and termination), walking at varying walking speed, walking while distracted, turning, task transitions.
  • Modeling: add handles to human model, optimization of movement
  • Modeling: design controller for targeted assistance, based on different biomechanical input signals and event detection algorithms
  • Data analysis: compare walking with to walking without rollators using available data

Supervisor: Dr. Lizeth Sloot
potential collaborator: Dr. Matt Millard


Simulation and analysis of failed sit-to-stance

About one third of adults above 65 years of age fall once a year. As falls are the number one cause for injury in older adults, it is imperative to provide this group with appropriate support to prevent falls. To develop such support, we need a thorough understanding of why and how older adults fall. This would require detailed evaluated of the mechanics of typical falls during for instance standing up from a chair or walking around with a rollator. Unfortunately, limited data is available given the obvious restrictions on working with frail elderly in fall studies. As actual footage of falls is available, we aim to replicate different “typical” falls from this data, while measuring motion, forces, and EMG.

During biomechanical evaluations in an ongoing study, failed attempt of sit-to-stand and unbalance during walking are captured. The low incidence as well as the difference between the failures make them hard to study, but not less interesting to further evaluate!

(potential) Tasks:

  • Biomechanics measurement (potential: motion capture, forces / pressure insoles, EMG) of simulated falls, design of this “fall” replicating protocol focusing on younger participants
  • Data analysis: evaluation of failed sit-to-stance transitions and walking instabilities (comparing walking with and without a dual task) in older adults based on existing data
  • Integrate data of other databases of fall data to test stability metrics

Supervisors: Dr. Matt Millard & Dr. Lizeth Sloot


Lower-limb Exoskeleton to restore mobility in elderly

While exoskeletons have been applied with great success to the restoration of standing and walking ability to spinal cord injury, limited studies designed and evaluated exoskeleton support for frail older adults. In this project we adapt an existing exoskeleton (Twin Exoskeleton, ITT) to match the needs of older adults. In addition, aim to evaluate interaction forces and comfort between the user and the device.

An often articulated but sparsely addressed question relates to the habituation to assistive devices such as exoskeletons: how long does it take younger and especially older adults to “get used” to the exoskeleton and the provided support? The answers to these questions are not only valuable for our general understanding of how we learn to walk from a motor control perspective but have implications for further prototyping and biomechanical studies evaluating and tuning exoskeleton support in different populations.

(potential) Tasks:

  • Biomechanics measurement (potential: motion capture, contact forces, EMG) of walking with and without the exoskeleton during different motions, including walking, turning, sit-to-stand
  • Motor control: design and measurement of habituation protocol
  • Develop and test different (bioinspired) controllers to drive support
  • Modeling: simulation and optimal control of movement using human+exoskeleton model
  • Design buckle-transducers to measure interaction forces between exoskeleton and human

Supervisor: Giorgos Marinou
Collaborators: Dr. Matt Millard & Dr. Lizeth Sloot


Dynamic Balance Model Benchmarking

Balance is a complex process that requires coordination of the entire body to regulate the linear momentum, angular momentum, and foot placement. There are two models of balance in the literature: the extrapolated center of mass, and the foot-placement estimator. Both models make certain mechanical assumptions of the motion. Both models have received only a limited amount comparison to experimental data to see if the person takes a step when the models would predict that the person, or bipedal robot, actually does take a step (or falls).

(potential) Tasks:

  • Develop a C++ implementation of both models in RBDL (robotics focused) and/or OpenSim (biomechanics focused).
  • Curate existing trials in which a participant loses their balance. We have some data in house for this, and there is some (potential) data in the literature. Analyze the data using the models to see how the predictions of the models compares to reality.
  • Extend the analytical methods that we’ve developed. For example to determine how much each body segment contributes to the location of the dynamic balance point.

Supervisor: Dr. Matt Millard
Collaborator: Dr. Lizeth Sloot

Relevant Literature:
Sloot LH, Millard M, Werner C, Mombaur K. Slow but steady: similar sit-to-stand balance at seat-off in older versus younger adults. Frontiers in Sports and Active Living. 2020;2:144.