Journal of Movement Disorders

Original Articles

Quantitative Gait Analysis in Patients with Huntington’s Disease: Seon Jong Pyo, Hanjun Kim, Il Soo Kim, Young-Min Park, Mi-Jung Kim, Hye Mi Lee, Seong-Beom Koh; J Mov Disord. 2017;10(3):140-144. Published online August 31, 2017; DOI: https://doi.org/10.14802/jmd.17041

7,249 View
141 Download
17 Web of Science
18 Crossref

Objective
Gait disturbance is the main factor contributing to a negative impact on quality of life in patients with Huntington’s disease (HD). Understanding gait features in patients with HD is essential for planning a successful gait strategy. The aim of this study was to investigate temporospatial gait parameters in patients with HD compared with healthy controls.
Methods
We investigated 7 patients with HD. Diagnosis was confirmed by genetic analysis, and patients were evaluated with the Unified Huntington’s Disease Rating Scale (UHDRS). Gait features were assessed with a gait analyzer. We compared the results of patients with HD to those of 7 age- and sex-matched normal controls.
Results
Step length and stride length were decreased and base of support was increased in the HD group compared to the control group. In addition, coefficients of variability for step and stride length were increased in the HD group. The HD group showed slower walking velocity, an increased stance/swing phase in the gait cycle and a decreased proportion of single support time compared to the control group. Cadence did not differ significantly between groups. Among the UHDRS subscores, total motor score and total behavior score were positively correlated with step length, and total behavior score was positively correlated with walking velocity in patients with HD.
Conclusion
Increased variability in step and stride length, slower walking velocity, increased stance phase, and decreased swing phase and single support time with preserved cadence suggest that HD gait patterns are slow, ataxic and ineffective. This study suggests that quantitative gait analysis is needed to assess gait problems in HD.

Citations

Citations to this article as recorded by

Sensor-Based Locomotion Data Mining for Supporting the Diagnosis of Neurodegenerative Disorders: A Survey
Samaneh Zolfaghari, Sumaiya Suravee, Daniele Riboni, Kristina Yordanova
ACM Computing Surveys.2024; 56(1): 1. CrossRef
The semicircular canal function is preserved with little impact on falls in patients with mild Parkinson's disease
Jun-Pyo Hong, Hanim Kwon, Euyhyun Park, Sun-Uk Lee, Chan-Nyoung Lee, Byung-Jo Kim, Ji-Soo Kim, Kun-Woo Park
Parkinsonism & Related Disorders.2024; 118: 105933. CrossRef
Gene-dosage- and sex-dependent differences in the prodromal-Like phase of the F344tgHD rat model for Huntington disease
Veronika Ratz-Wirsching, Johanna Habermeyer, Sandra Moceri, Julia Harrer, Christoph Schmitz, Stephan von Hörsten
Frontiers in Neuroscience.2024;[Epub] CrossRef
Wearable sensors and features for diagnosis of neurodegenerative diseases: A systematic review
Huan Zhao, Junyi Cao, Junxiao Xie, Wei-Hsin Liao, Yaguo Lei, Hongmei Cao, Qiumin Qu, Chris Bowen
DIGITAL HEALTH.2023; 9: 205520762311735. CrossRef
Spatiotemporal Gait Parameters in Adults With Premanifest and Manifest Huntington’s Disease: A Systematic Review
Sasha Browning, Stephanie Holland, Ian Wellwood, Belinda Bilney
Journal of Movement Disorders.2023; 16(3): 307. CrossRef
Walking pattern analysis using GAIT cycles and silhouettes for clinical applications
S.M.H. Sithi Shameem Fathima, K.A. Jyotsna, Thiruveedula Srinivasulu, Kande Archana, M. Tulasi rama, S. Ravichand
Measurement: Sensors.2023; 30: 100893. CrossRef
Human Gait Analysis in Neurodegenerative Diseases: A Review
Grazia Cicirelli, Donato Impedovo, Vincenzo Dentamaro, Roberto Marani, Giuseppe Pirlo, Tiziana R. D'Orazio
IEEE Journal of Biomedical and Health Informatics.2022; 26(1): 229. CrossRef
Development of Neuro-Degenerative Diseases’ Gait Classification Algorithm Using Convolutional Neural Network and Wavelet Coherence Spectrogram of Gait Synchronization
Febryan Setiawan, An-Bang Liu, Che-Wei Lin
IEEE Access.2022; 10: 38137. CrossRef
Artificial intelligence in neurodegenerative diseases: A review of available tools with a focus on machine learning techniques
Alexandra-Maria Tăuţan, Bogdan Ionescu, Emiliano Santarnecchi
Artificial Intelligence in Medicine.2021; 117: 102081. CrossRef
Identification of Neurodegenerative Diseases Based on Vertical Ground Reaction Force Classification Using Time–Frequency Spectrogram and Deep Learning Neural Network Features
Febryan Setiawan, Che-Wei Lin
Brain Sciences.2021; 11(7): 902. CrossRef
The effects of dual-task cognitive interference on gait and turning in Huntington’s disease
Nicollette L. Purcell, Jennifer G. Goldman, Bichun Ouyang, Yuanqing Liu, Bryan Bernard, Joan A. O’Keefe, Pedro Gonzalez-Alegre
PLOS ONE.2020; 15(1): e0226827. CrossRef
Gait variability as digital biomarker of disease severity in Huntington’s disease
Heiko Gaßner, Dennis Jensen, F. Marxreiter, Anja Kletsch, Stefan Bohlen, Robin Schubert, Lisa M. Muratori, Bjoern Eskofier, Jochen Klucken, Jürgen Winkler, Ralf Reilmann, Zacharias Kohl
Journal of Neurology.2020; 267(6): 1594. CrossRef
Evaluation of Vertical Ground Reaction Forces Pattern Visualization in Neurodegenerative Diseases Identification Using Deep Learning and Recurrence Plot Image Feature Extraction
Che-Wei Lin, Tzu-Chien Wen, Febryan Setiawan
Sensors.2020; 20(14): 3857. CrossRef
Cerebral dopamine neurotrophic factor (CDNF) protects against quinolinic acid-induced toxicity in in vitro and in vivo models of Huntington’s disease
P. Stepanova, V. Srinivasan, D. Lindholm, M. H. Voutilainen
Scientific Reports.2020;[Epub] CrossRef
Rapid and robust patterns of spontaneous locomotor deficits in mouse models of Huntington’s disease
Taneli Heikkinen, Timo Bragge, Niina Bhattarai, Teija Parkkari, Jukka Puoliväli, Outi Kontkanen, Patrick Sweeney, Larry C. Park, Ignacio Munoz-Sanjuan, Yuqing Li
PLOS ONE.2020; 15(12): e0243052. CrossRef
Rule based classification of neurodegenerative diseases using data driven gait features
Kartikay Gupta, Aayushi Khajuria, Niladri Chatterjee, Pradeep Joshi, Deepak Joshi
Health and Technology.2019; 9(4): 547. CrossRef
Discovery of Arginine Ethyl Ester as Polyglutamine Aggregation Inhibitor: Conformational Transitioning of Huntingtin N-Terminus Augments Aggregation Suppression
Virender Singh, Kinjal A. Patel, Raj Kumar Sharma, Pratik R. Patil, Abhayraj S. Joshi, Rashmi Parihar, Thamarailingam Athilingam, Neeraj Sinha, Subramaniam Ganesh, Pradip Sinha, Ipsita Roy, Ashwani Kumar Thakur
ACS Chemical Neuroscience.2019; 10(9): 3969. CrossRef
Gait Biomarkers Classification by Combining Assembled Algorithms and Deep Learning: Results of a Local Study
Eddy Sánchez-DelaCruz, Roberto Weber, R. R. Biswal, Jose Mejía, Gandhi Hernández-Chan, Heberto Gómez-Pozos
Computational and Mathematical Methods in Medicine.2019; 2019: 1. CrossRef

Cognition and Visit-to-Visit Variability of Blood Pressure and Heart Rate in De Novo Patients with Parkinson’s Disease: Kyum-Yil Kwon, Seon Jong Pyo, Hye Mi Lee, Woo-Keun Seo, Seong-Beom Koh; J Mov Disord. 2016;9(3):144-151. Published online September 21, 2016; DOI: https://doi.org/10.14802/jmd.16012

13,374 View
122 Download
8 Web of Science
8 Crossref

Abstract PDF Supplementary Material

Objective
We sought to identify whether the characteristics of long-term visit-to-visit blood pressure (BP) and heart rate (HR) are related to baseline cognitive profiles in, Parkinson’s disease (PD).
Methods
We selected drug-naïve PD patients who visited our hospital at least 10 times with a baseline assessment of the Seoul neuropsychological battery. BP and HR were measured at each visit, and the variability of the systolic BP/diastolic BP (DBP) and HR was derived from the parameters of serial 10 office visits. Mild cognitive impairment (MCI) in PD patients was determined according to the proposed criteria with a cut-off value of z-score ≤ -2.
Results
Forty-seven patients with PD (mean follow-up duration = 22.3 months) were enrolled in the study. Compared with non-MCI PD patients, MCI PD patients revealed a significant increase in HR and/or variability in DBP.
Conclusion
This exploratory study showed that baseline cognition in drug-naïve PD patients might be related to the visit-to-visit variability of DBP and/or HR.

Citations

Citations to this article as recorded by

Association between the blood pressure variability and cognitive decline in Parkinson's disease
Yi Xiao, Tianmi Yang, Lingyu Zhang, Qianqian Wei, Ruwei Ou, Yanbing Hou, Kuncheng Liu, Junyu Lin, Qirui Jiang, Huifang Shang
Brain and Behavior.2023;[Epub] CrossRef
Cardiovascular autonomic dysfunction is associated with executive dysfunction and poorer quality of life in progressive supranuclear palsy-Richardson’s syndrome
Peng Liu, Yueting Chen, Bo Wang, Sheng Wu, Leilei Zeng, Zhidong Cen, Dehao Yang, Haotian Wang, Xinhui Chen, Lebo Wang, Zhiyuan Ouyang, Wei Luo
Journal of Clinical Neuroscience.2022; 96: 147. CrossRef
Blood Pressure Variability and Cognitive Function: a Scoping Review
Nur Fazidah Asmuje, Sumaiyah Mat, Phyo Kyaw Myint, Maw Pin Tan
Current Hypertension Reports.2022; 24(10): 375. CrossRef
Associations of cognitive dysfunction with motor and non-motor symptoms in patients with de novo Parkinson’s disease
Kyum-Yil Kwon, Suyeon Park, Rae On Kim, Eun Ji Lee, Mina Lee
Scientific Reports.2022;[Epub] CrossRef
Blood pressure variability is related to faster cognitive decline in ischemic stroke patients: PICASSO subanalysis
Yerim Kim, Jae-Sung Lim, Mi Sun Oh, Kyung-Ho Yu, Ji Sung Lee, Jong-Ho Park, Yong-Jae Kim, Joung-Ho Rha, Yang-Ha Hwang, Sung Hyuk Heo, Seong Hwan Ahn, Ju-Hun Lee, Sun U. Kwon
Scientific Reports.2021;[Epub] CrossRef
The correlation of blood pressure variability and cognitive function in hypertension patients: A meta‐analysis
Xiaojie Jin, Yi Lu, Peng Zhao
International Journal of Clinical Practice.2021;[Epub] CrossRef
Burden and correlates of cognitive impairment among hypertensive patients in Tanzania: a cross-sectional study
Pedro Pallangyo, Zabella S. Mkojera, Makrina Komba, Lucy R. Mgopa, Smita Bhalia, Henry Mayala, Salma Wibonela, Nsajigwa Misidai, Happiness J. Swai, Jalack Millinga, Ester Chavala, Peter R. Kisenge, Mohamed Janabi
BMC Neurology.2021;[Epub] CrossRef
Backward Gait is Associated with Motor Symptoms and Fear of Falling in Patients withDe NovoParkinson's Disease
Kyum-Yil Kwon, Suyeon Park, Hye Mi Lee, Young-Min Park, Jinhee Kim, Jaehwan Kim, Seong-Beom Koh
Journal of Clinical Neurology.2019; 15(4): 473. CrossRef

First
Prev
Page of 1
Next
Last

Search