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Gait, Freezing of Gait and Falls detection using wearable sensors; a systematic review

A.L. Silvade Lima, L.JW. Evers, T. Hahn, L. Bataille, J.L. Hamilton, M.A. Little, B.R. Bloem, M.J. Faber (Nijmegen, Netherlands)

Meeting: 2017 International Congress

Abstract Number: 652

Keywords: Gait disorders: Treatment, Interventions, Parkinsonism

Session Information

Date: Tuesday, June 6, 2017

Session Title: Technology

Session Time: 1:45pm-3:15pm

Location: Exhibit Hall C

Objective: An overview of the use of wearable systems to assess gait, freezing of gait (FOG) and falls in patients with Parkinson’s disease (PD). 

Background:  Despite the large number of studies that have investigated the use of wearable sensors to detect gait and gait disturbances such as FOG and falls, little consensus has been achieved regarding device usage methodologies. 

Methods: A systematic search in the PubMed and Web of Science databases was performed using a group of concept key words. The final search was performed in November 2016, and articles were selected based upon a set of eligibility criteria, and data extraction was performed using a predefined table.

Results: In total 39 articles were selected. Of those, 21 related to FOG, 14 to gait and 4 to falls. FOG studies were performed in either laboratory or home settings, with the shin as most preferable location and accelerometer as the most used sensor type. Validity measures ranged from 73-100% for sensitivity and 67-100% for specificity. Falls and fall risk articles were all home-based, mostly using one sensor containing accelerometers, in various positions. Most articles assessing gait consisted of pre-structured tasks performed in a laboratory environment. Gyroscopes and accelerometers were most commonly used, placed at the shin and/or axial body locations. Gait was detected with a sensitivity of 84-100% and specificity of 75-99%. By quantifying gait into parameters, some systems were able to detect differences between groups (PD-ON/PD-OFF and PD/non-PD). 

Conclusions:

Despite the promising validation initiatives reported in these studies, they were all performed in a relatively small sample sizes, and there was a lack of consistency in outcomes measured and results reported. Given these limitations, the validation of sensor-derived assessments of PD features would benefit from increased collaboration among researchers, aligning data collection protocols, and merging dataset. 

To cite this abstract in AMA style:

A.L. Silvade Lima, L.JW. Evers, T. Hahn, L. Bataille, J.L. Hamilton, M.A. Little, B.R. Bloem, M.J. Faber. Gait, Freezing of Gait and Falls detection using wearable sensors; a systematic review [abstract]. Mov Disord. 2017; 32 (suppl 2). https://www.mdsabstracts.org/abstract/gait-freezing-of-gait-and-falls-detection-using-wearable-sensors-a-systematic-review/. Accessed June 15, 2025.
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