01 / 2021 – 06 / 2021
Walking is an important part of a self-determined life. Especially for older people, gait is an indicator of physical well-being . Consequently, overground gait analysis is used in several studies to assess overall health, fall risk, and disease progression, as well as other critical health issues [2, 3]. However, considering gait parameters from stair climbing may help to paint a more accurate picture , as stair climbing performance can differ significantly from level-ground walking performance due to additional demands on the balance and control system, greater emphasis on lower limb muscle strength, or even psychological factors including fear of falling [5, 6, 7]. Since there are obstacles using video-based motion-capture systems or computerized walkways for gait analysis on stairs in real-world settings, it is preferable to use wearable inertial measurement units (IMUs) instead. In addition to being comparably reliable , IMUs are less costly, small and light weight, and therefore, offer the possibility to unobtrusively measure gait even in free-living environments.
Previous studies concerning gait analysis on stairs have shown that conclusions about the health of the subjects can be derived from stair ambulation parameters. The methods ranged from simple measurement of the time needed to ascent or descent a given set of stairs  to more complicated setups consisting of multiple IMUs attached to the lower back and ankle to evaluate fall risk  or to the sternum to develop objective indices for clinical application to assess stair ascent in neurologically-impaired patients . Studies using IMUs attached to the shank have successfully distinguished stair ascent from stair descent and level-walking [10, 11] and detected initial contact and terminal contact gait events during stair walking . These results suggest that further investigation into relevant parameters during stair ambulation will contribute to an objective assessment of patients’ gait. In particular, working with foot-worn IMUs instead of mounting them to the anterior side of the shank – or other body parts even further away from the feet – provides the opportunity to extract additional parameters such as foot angles from the data and thereby achieve higher bio-mechanical resolution.
So far no algorithm specifically designed for gait event detection for stair ambulation with footworn IMUs has been developed and due to the unique physical constraints implied by stair steps and changing stride patterns, common stride event detection algorithms developed for level ground walking approaches with foot-worn IMUs, as introduced by Rampp et. al. , may not produce reliable results in stair negotiation. Nevertheless, a robust detection of standardized events like initial contact as well as terminal contact is desirable to extract detailed stair stride parameters including support times or swing duration. Such parameters can then help to gain a deeper insight into a patient’s gait and motor impairments during stair negotiation or to identify different stair ambulation strategies.
Currently there is no available dataset of stair climbing based on foot-worn IMUs together with gait event references in free-living environments. Therefore, the aim of this thesis is first to conduct a study to collect real world stair climbing data with video-based and pressure sensor based stride event references and second to develop and evaluate respective event detection algorithms based on the acquired dataset. The results and findings from this work could then be applied to existing free-living patient data (FallRiskPD dataset), for example to better assess the risk of falls in Parkinson’s Disease patients.
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