Details

Autor(en) / Beteiligte

• Martindale, Christine F.
• Strauss, Martin
• Gassner, Heiko
• List, Julia
• Muller, Meinard
• Klucken, Jochen
• Kohl, Zacharias
• Eskofier, Bjoern M.

Titel

Segmentation of gait sequences using inertial sensor data in hereditary spastic paraplegia

Ist Teil von

• 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017, Vol.2017, p.1266-1269

Ort / Verlag

IEEE

Erscheinungsjahr

2017

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• In this paper we use foot-mounted inertial measurement units (IMU) as a mobile solution to measure the gait of 21 HSP patients while performing a 4 by 10 m walk at self-selected pace. Two algorithms common to other gait analysis solutions, the hidden Markov model (HMM) and dynamic time warping (DTW), were applied to these signals in order to investigate their effectiveness when faced with the heterogeneous nature and range of foot strike techniques of HSP gait, sometimes even lacking a heel strike. Using a nested cross validation for parameter choice and validation, the HMM was found to be superior for segmentation purposes with a mean segmentation error of 0.10 ± 0.05 s.