Title
Segmentation Of Gait Sequences Using Inertial Sensor Data In Hereditary Spastic Paraplegia
Abstract
Gait analysis is an important tool for diagnosis, monitoring and treatment of neurological diseases. Among these are hereditary spastic paraplegias (HSPs) whose main characteristic is heterogeneous gait disturbance. So far HSP gait has been analysed in a limited number of studies, and within a laboratory set up only. Although the rarity of orphan diseases often limits larger scale studies, the investigation of these diseases is still important, not only to the affect population, but also for other diseases which share gait characteristics.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.Stride segmentation of such a diverse dataset is the first step towards creating a clinically relevant system which could assist physicians working with HSP patients by providing objective, automated gait parameters. To the best of the authors' knowledge, this is the first paper to investigate solutions for mobile gait analysis of patients affected by HSPs. Ultimately, automated, mobile gait analysis of HSP patients would allow ongoing and long term monitoring, providing useful insights into this orphan disease.
Year
DOI
Venue
2017
10.1109/EMBC.2017.8037062
2017 39TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Field
DocType
Volume
Population,Spastic Paraplegias,Gait,Segmentation,Computer science,Orphan diseases,Gait analysis,Physical medicine and rehabilitation,Gait Disturbance,Hereditary spastic paraplegia
Conference
2017
ISSN
Citations 
PageRank 
1094-687X
0
0.34
References 
Authors
6
8
Name
Order
Citations
PageRank
Christine F. Martindale130.78
Martin Strauss27711.49
Heiko Gassner3605.87
Julia List400.68
Meinard Müller51553130.84
Jochen Klucken6587.46
Zacharias Kohl701.01
Bjoern Eskofier817044.31