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

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.

[1]  Björn Eskofier,et al.  Inertial Sensor-Based Stride Parameter Calculation From Gait Sequences in Geriatric Patients , 2015, IEEE Transactions on Biomedical Engineering.

[2]  Günther Deuschl,et al.  Methylphenidate fails to improve gait and muscle tone in patients with sporadic and hereditary spastic paraplegia , 2006, Movement disorders : official journal of the Movement Disorder Society.

[3]  C. McDermott,et al.  Hereditary spastic paraparesis: a review of new developments , 2000, Journal of neurology, neurosurgery, and psychiatry.

[4]  Angelo M. Sabatini,et al.  Assessment of walking features from foot inertial sensing , 2005, IEEE Transactions on Biomedical Engineering.

[5]  Zacharias Kohl,et al.  Hereditary spastic paraplegia: Clinicogenetic lessons from 608 patients , 2016, Annals of neurology.

[6]  Angelo M. Sabatini,et al.  A Machine Learning Framework for Gait Classification Using Inertial Sensors: Application to Elderly, Post-Stroke and Huntington’s Disease Patients , 2016, Sensors.

[7]  Ralf Mikut,et al.  Gait analysis may help to distinguish hereditary spastic paraplegia from cerebral palsy. , 2011, Gait & posture.

[8]  J. Fink,et al.  Chapter 119 – Hereditary Spastic Paraplegia , 2013 .

[9]  Manuela Galli,et al.  3D gait analysis in patients with hereditary spastic paraparesis and spastic diplegia: a kinematic, kinetic and EMG comparison. , 2011, European journal of paediatric neurology : EJPN : official journal of the European Paediatric Neurology Society.

[10]  J Kassubek,et al.  The Spastic Paraplegia Rating Scale (SPRS) , 2006, Neurology.

[11]  J. Fink,et al.  Hereditary spastic paraplegia: clinico-pathologic features and emerging molecular mechanisms , 2013, Acta Neuropathologica.

[12]  Björn Eskofier,et al.  Stride Segmentation during Free Walk Movements Using Multi-Dimensional Subsequence Dynamic Time Warping on Inertial Sensor Data , 2015, Sensors.

[13]  Elmar Nöth,et al.  Java Visual Speech Components for Rapid Application Development of GUI Based Speech Processing Applications , 2011, INTERSPEECH.

[14]  Yoram Singer,et al.  The Hierarchical Hidden Markov Model: Analysis and Applications , 1998, Machine Learning.

[15]  J. Kassubek,et al.  Disease severity affects quality of life of hereditary spastic paraplegia patients , 2012, European journal of neurology.

[16]  Eduardo Palermo,et al.  Gait Partitioning Methods: A Systematic Review , 2016, Sensors.

[17]  M Mancuso,et al.  Robotic gait training improves motor skills and quality of life in hereditary spastic paraplegia. , 2015, NeuroRehabilitation.

[18]  G. Deuschl,et al.  Gait analysis of sporadic and hereditary spastic paraplegia , 2004, Journal of Neurology.

[19]  T Claire Davies,et al.  The effect of hydrotherapy treatment on gait characteristics of hereditary spastic paraparesis patients. , 2014, Gait & posture.

[20]  Han Gil Seo,et al.  Robot‐Assisted Gait Training in a Patient With Hereditary Spastic Paraplegia , 2015, PM & R : the journal of injury, function, and rehabilitation.

[21]  K Turcot,et al.  Full body gait analysis may improve diagnostic discrimination between hereditary spastic paraplegia and spastic diplegia: a preliminary study. , 2013, Research in developmental disabilities.

[22]  Francesco Lacquaniti,et al.  Gait Patterns in Patients with Hereditary Spastic Paraparesis , 2016, PloS one.