Literature DB >> 23797284

Accelerometry-based gait analysis and its application to Parkinson's disease assessment- part 2: a new measure for quantifying walking behavior.

Mitsuru Yoneyama, Yosuke Kurihara, Kajiro Watanabe, Hiroshi Mitoma.   

Abstract

Gait analysis is a valuable tool for obtaining quantitative information on motor deficits in Parkinson's disease (PD). Since the characteristic gait patterns of PD patients may not be fully identified by brief examination in a clinic, long-term, and unobtrusive monitoring of their activities is essential, especially in a nonclinical setting. This paper describes a single accelerometer-based gait analysis system for the assessment of ambulatory gait properties. Acceleration data were recorded continuously for up to 24 h from normal and PD subjects, from which gait peaks were picked out and the relationship between gait cycle and vertical gait acceleration was evaluated. By fitting a model equation to the relationships, a quantitative index was obtained for characterizing the subjects' walking behavior. The averaged index for PD patients with gait disorder was statistically smaller than the value for normal subjects. The proposed method could be used to evaluate daily gait characteristics and thus contribute to a more refined diagnosis and treatment of the disease.

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Year:  2013        PMID: 23797284     DOI: 10.1109/TNSRE.2013.2268251

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  21 in total

1.  Association of daily physical activity with cognition and mood disorders in treatment-naive patients with early-stage Parkinson's disease.

Authors:  Hiroo Terashi; Takeshi Taguchi; Yuki Ueta; Hiroshi Mitoma; Hitoshi Aizawa
Journal:  J Neural Transm (Vienna)       Date:  2019-09-30       Impact factor: 3.575

2.  Machine Learning Classifiers to Evaluate Data From Gait Analysis With Depth Cameras in Patients With Parkinson's Disease.

Authors:  Beatriz Muñoz-Ospina; Daniela Alvarez-Garcia; Hugo Juan Camilo Clavijo-Moran; Jaime Andrés Valderrama-Chaparro; Melisa García-Peña; Carlos Alfonso Herrán; Christian Camilo Urcuqui; Andrés Navarro-Cadavid; Jorge Orozco
Journal:  Front Hum Neurosci       Date:  2022-05-19       Impact factor: 3.473

Review 3.  How Wearable Sensors Can Support Parkinson's Disease Diagnosis and Treatment: A Systematic Review.

Authors:  Erika Rovini; Carlo Maremmani; Filippo Cavallo
Journal:  Front Neurosci       Date:  2017-10-06       Impact factor: 4.677

4.  Noisy interlimb coordination can be a main cause of freezing of gait in patients with little to no parkinsonism.

Authors:  Takao Tanahashi; Tomohisa Yamamoto; Takuyuki Endo; Harutoshi Fujimura; Masaru Yokoe; Hideki Mochizuki; Taishin Nomura; Saburo Sakoda
Journal:  PLoS One       Date:  2013-12-31       Impact factor: 3.240

5.  Estimation of step-by-step spatio-temporal parameters of normal and impaired gait using shank-mounted magneto-inertial sensors: application to elderly, hemiparetic, parkinsonian and choreic gait.

Authors:  Diana Trojaniello; Andrea Cereatti; Elisa Pelosin; Laura Avanzino; Anat Mirelman; Jeffrey M Hausdorff; Ugo Della Croce
Journal:  J Neuroeng Rehabil       Date:  2014-11-11       Impact factor: 4.262

Review 6.  Remote Physical Activity Monitoring in Neurological Disease: A Systematic Review.

Authors:  Valerie A J Block; Erica Pitsch; Peggy Tahir; Bruce A C Cree; Diane D Allen; Jeffrey M Gelfand
Journal:  PLoS One       Date:  2016-04-28       Impact factor: 3.240

7.  Using Commercial Activity Monitors to Measure Gait in Patients with Suspected iNPH: Implications for Ambulatory Monitoring.

Authors:  Shiv Gaglani; Jessica Moore; M Ryan Haynes; Jamie B Hoffberger; Daniele Rigamonti
Journal:  Cureus       Date:  2015-11-17

8.  Intra-rater and inter-rater reliability of the portable gait rhythmogram in post-stroke patients.

Authors:  Ryuji Miyata; Shuji Matsumoto; Seiji Miura; Kentaro Kawamura; Tomohiro Uema; Kodai Miyara; Ayana Niibo; Tadashi Ogura; Megumi Shimodozono
Journal:  J Phys Ther Sci       Date:  2017-05-16

9.  Synchronous wearable wireless body sensor network composed of autonomous textile nodes.

Authors:  Peter Vanveerdeghem; Patrick Van Torre; Christiaan Stevens; Jos Knockaert; Hendrik Rogier
Journal:  Sensors (Basel)       Date:  2014-10-09       Impact factor: 3.576

10.  Long-term Monitoring Gait Analysis Using a Wearable Device in Daily Lives of Patients with Parkinson's Disease: The Efficacy of Selegiline Hydrochloride for Gait Disturbance.

Authors:  Mutsumi Iijima; Hiroshi Mitoma; Shinichiro Uchiyama; Kazuo Kitagawa
Journal:  Front Neurol       Date:  2017-10-24       Impact factor: 4.003

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