Literature DB >> 21999184

Analysis of lower limb bradykinesia in Parkinson's disease patients.

Ji-Won Kim1, Yuri Kwon, Yu-Mi Kim, Hong-Young Chung, Gwang-Moon Eom, Jae-Hoon Jun, Jeong-Whan Lee, Seong-Beom Koh, Byung Kyu Park, Dae-Kyu Kwon.   

Abstract

AIM: Bradykinesia of the lower limb is an important limiting factor of the quality of life in parkinsonian patients. This study aims to develop quantitative measures of bradykinesia and to investigate the possible dissociation of amplitude and velocity measures and their dependence on movement direction during toe-tapping.
METHODS: Subjects included 39 patients with PD, as well as 14 healthy control subjects. A gyrosensor on the dorsum of a foot was used to measure ankle joint movement during toe-tapping. Four representations (root-mean square, mean peak, coefficient of variation in peaks, peak in the last 5 s) for each of amplitude and velocity and for each of plantar flexion and dorsiflexion movement of toe-tapping were investigated. Outcome measures were compared between patients and controls, and their correlations with clinical scores were investigated. Category distributions of outcome measures in patients were analyzed.
RESULTS: All outcome measures were smaller in patients than in controls (P < 0.001) and correlated well with clinical scores (P < 0.01). The mean peak of plantar-flexion velocity and variation of dorsiflexion velocity best represented the clinical toe-tapping score (r = 0.72-0.81). All clinical scores showed better correlation with velocity than with amplitude, and velocity was more affected (dispersed from the performance of controls) than amplitude. Movement directions had a slight effect on the results; specifically, the magnitude measures better correlated during plantar flexion and the variation measure better correlated during dorsiflexion.
CONCLUSION: The suggested measures represented clinical scores well and are expected to be helpful in clinical diagnosis of lower limb bradykinesia. Possible dissociations of amplitude and speed impairments and of movement directions in PD deserve further investigation.
© 2011 Japan Geriatrics Society.

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Year:  2011        PMID: 21999184     DOI: 10.1111/j.1447-0594.2011.00761.x

Source DB:  PubMed          Journal:  Geriatr Gerontol Int        ISSN: 1447-0594            Impact factor:   2.730


  9 in total

Review 1.  Using wearables to assess bradykinesia and rigidity in patients with Parkinson's disease: a focused, narrative review of the literature.

Authors:  Itay Teshuva; Inbar Hillel; Eran Gazit; Nir Giladi; Anat Mirelman; Jeffrey M Hausdorff
Journal:  J Neural Transm (Vienna)       Date:  2019-05-22       Impact factor: 3.575

2.  Smartphone-Based Estimation of Item 3.8 of the MDS-UPDRS-III for Assessing Leg Agility in People With Parkinson's Disease.

Authors:  Luigi Borzi; Marilena Varrecchia; Stefano Sibille; Gabriella Olmo; Carlo Alberto Artusi; Margherita Fabbri; Mario Giorgio Rizzone; Alberto Romagnolo; Maurizio Zibetti; Leonardo Lopiano
Journal:  IEEE Open J Eng Med Biol       Date:  2020-05-08

3.  Factors influencing obstacle crossing performance in patients with Parkinson's disease.

Authors:  Ying-Yi Liao; Yea-Ru Yang; Yih-Ru Wu; Ray-Yau Wang
Journal:  PLoS One       Date:  2014-01-13       Impact factor: 3.240

4.  A Wearable System to Objectify Assessment of Motor Tasks for Supporting Parkinson's Disease Diagnosis.

Authors:  Erika Rovini; Carlo Maremmani; Filippo Cavallo
Journal:  Sensors (Basel)       Date:  2020-05-05       Impact factor: 3.576

5.  Quantitative measures of postural tremor at the upper limb joints in patients with essential tremor.

Authors:  Do-Young Kwon; Yu-Ri Kwon; Yoon-Hyeok Choi; Gwang-Moon Eom; Junghyuk Ko; Ji-Won Kim
Journal:  Technol Health Care       Date:  2020       Impact factor: 1.285

6.  Vision-based assessment of parkinsonism and levodopa-induced dyskinesia with pose estimation.

Authors:  Michael H Li; Tiago A Mestre; Susan H Fox; Babak Taati
Journal:  J Neuroeng Rehabil       Date:  2018-11-06       Impact factor: 4.262

7.  Age-related differences in the quantitative analysis of the finger tapping task.

Authors:  Yu-Ri Kwon; Junghyuk Ko; Ryun-Hee Lee; Gwang-Moon Eom; Ji-Won Kim
Journal:  Technol Health Care       Date:  2022       Impact factor: 1.205

8.  User Profiling to Enhance Clinical Assessment and Human-Robot Interaction: A Feasibility Study.

Authors:  Laura Fiorini; Luigi Coviello; Alessandra Sorrentino; Daniele Sancarlo; Filomena Ciccone; Grazia D'Onofrio; Gianmaria Mancioppi; Erika Rovini; Filippo Cavallo
Journal:  Int J Soc Robot       Date:  2022-07-08       Impact factor: 3.802

Review 9.  Technologies Assessing Limb Bradykinesia in Parkinson's Disease.

Authors:  Hasan Hasan; Dilan S Athauda; Thomas Foltynie; Alastair J Noyce
Journal:  J Parkinsons Dis       Date:  2017       Impact factor: 5.568

  9 in total

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