Literature DB >> 29962192

Computerized gait analysis with inertial sensor in the management of idiopathic normal pressure hydrocephalus.

Pier Paolo Panciani1, Karol Migliorati2, Andrea Muratori2, Marco Gelmini2, Alessandro Padovani3, Marco Fontanella2.   

Abstract

BACKGROUND: Gait disturbance (GD) is usually the first and most prominent symptom observed in idiopathic normal pressure hydrocephalus (iNPH). The reversibility of symptoms is related to early diagnosis and treatment. Nowadays early recognition of patients is challenging because GD in the elderly is frequently neglected, leading to late diagnosis and increased disability. In addition, GD is generally assessed by clinical evaluation since computerized gait analysis methods are rarely available. In the present study, we demonstrate the clinical application of an inertial sensor system for gait analysis in iNPH. AIM: The primary aim was to test the sensor performance in quantifying impairment in gait parameters in iNPH. The secondary aim was to detect a range of improvement after CSF subtraction test, which could be considered as predictive of favorable shunt response.
DESIGN: We performed a case-control prospective study from March 2012 to May 2014.
SETTING: Inpatients at the Division of Neurology, Department of Clinical and Experimental Sciences, Brescia. POPULATION: We enrolled 79 patients with clinical and radiological findings of iNPH and 300 healthy adults over 70 years old without GD as a control group.
METHODS: We performed gait analysis, CSF Tap Test (TT), and shunt surgery in all patients with a diagnosis of iNPH according to the International Guidelines. According to clinical outcomes, we divided patients in responsive (group A) and non-responsive (group B). We then compared pre-operative gait analysis of group A with the control group, and calculated the percentage of improvement after TT between group A and group B.
RESULTS: Shunt surgery was performed in 52 patients. After 3 months, 35 patients (group A: 67.3%) showed a positive response to shunt. We quantified the impaired gait parameters in iNPH and assessed the differences with controls. Improvement of speed, stride length and double support time after TT was predictive of positive shunt response.
CONCLUSIONS: The proposed inertial sensor system is a reliable and easy-to-use system for early detection of iNPH and may be used in any clinical setting. CLINICAL REHABILITATION IMPACT: Identification of a GD pattern for iNPH, especially in rehabilitation, may be useful for recognizing patients who are candidates for surgery, thus avoiding permanent disability.

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Year:  2018        PMID: 29962192     DOI: 10.23736/S1973-9087.18.04949-3

Source DB:  PubMed          Journal:  Eur J Phys Rehabil Med        ISSN: 1973-9087            Impact factor:   2.874


  4 in total

1.  Quantitative Evaluation of Gait Changes Using APDM Inertial Sensors After the External Lumbar Drain in Patients With Idiopathic Normal Pressure Hydrocephalus.

Authors:  Mengmeng He; Zhenyu Qi; Yunxiang Shao; Hui Yao; Xuewen Zhang; Yang Zhang; Yu Shi; Qinzhi E; Chengming Liu; Hongwei Hu; Jiangang Liu; Xiaoou Sun; Zhong Wang; Yulun Huang
Journal:  Front Neurol       Date:  2021-07-08       Impact factor: 4.003

2.  Guidelines for Management of Idiopathic Normal Pressure Hydrocephalus (Third Edition): Endorsed by the Japanese Society of Normal Pressure Hydrocephalus.

Authors:  Madoka Nakajima; Shigeki Yamada; Masakazu Miyajima; Kazunari Ishii; Nagato Kuriyama; Hiroaki Kazui; Hideki Kanemoto; Takashi Suehiro; Kenji Yoshiyama; Masahiro Kameda; Yoshinaga Kajimoto; Mitsuhito Mase; Hisayuki Murai; Daisuke Kita; Teruo Kimura; Naoyuki Samejima; Takahiko Tokuda; Mitsunobu Kaijima; Chihiro Akiba; Kaito Kawamura; Masamichi Atsuchi; Yoshihumi Hirata; Mitsunori Matsumae; Makoto Sasaki; Fumio Yamashita; Shigeki Aoki; Ryusuke Irie; Hiroji Miyake; Takeo Kato; Etsuro Mori; Masatsune Ishikawa; Isao Date; Hajime Arai
Journal:  Neurol Med Chir (Tokyo)       Date:  2021-01-15       Impact factor: 1.742

3.  Development of Smartphone Application for Markerless Three-Dimensional Motion Capture Based on Deep Learning Model.

Authors:  Yukihiko Aoyagi; Shigeki Yamada; Shigeo Ueda; Chifumi Iseki; Toshiyuki Kondo; Keisuke Mori; Yoshiyuki Kobayashi; Tadanori Fukami; Minoru Hoshimaru; Masatsune Ishikawa; Yasuyuki Ohta
Journal:  Sensors (Basel)       Date:  2022-07-14       Impact factor: 3.847

4.  The effects of cerebrospinal fluid tap-test on idiopathic normal pressure hydrocephalus: an inertial sensors based assessment.

Authors:  Alberto Ferrari; David Milletti; Giulia Giannini; Sabina Cevoli; Federico Oppi; Giorgio Palandri; Luca Albini-Riccioli; Paolo Mantovani; Laura Anderlucci; Pietro Cortelli; Lorenzo Chiari
Journal:  J Neuroeng Rehabil       Date:  2020-01-16       Impact factor: 4.262

  4 in total

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