Evaluation of the IngVaL Pedobarography System for Monitoring of Walking Speed.
10.4258/hir.2018.24.2.118
- Author:
Per Anders Rickard HELLSTROM
1
;
Anna ÅKERBERG
;
Martin EKSTRÖM
;
Mia FOLKE
Author Information
1. Embedded Sensor Systems for Health at the School of Innovation, Design and Engineering, Mälardalen University, Västerås, Sweden. per.hellstrom@mdh.se
- Publication Type:Original Article
- Keywords:
Humans;
Movement;
Foot;
Walking;
Walking Speed
- MeSH:
Aged;
Foot;
Geographic Information Systems;
Humans;
Methods;
Walking*
- From:Healthcare Informatics Research
2018;24(2):118-124
- CountryRepublic of Korea
- Language:English
-
Abstract:
OBJECTIVES: Walking speed is an important component of movement and is a predictor of health in the elderly. Pedobarography, the study of forces acting between the plantar surface of the foot and a supporting surface, is an approach to estimating walking speed even when no global positioning system signal is available. The developed portable system, Identifying Velocity and Load (IngVaL), is a cost effective alternative to commercially available pedobarography systems because it only uses three force sensing resistors. In this study, the IngVaL system was evaluated. The three variables investigated in this study were the sensor durability, the proportion of analyzable steps, and the linearity between the system output and the walking speed. METHODS: Data was collected from 40 participants, each of whom performed five walks at five different self-paced walking speeds. The linearity between the walking speed and step frequency measured with R2 values was compared for the walking speed obtained ‘A’ only using amplitude data from the force sensors, ‘B’ that obtained only using the step frequency, and ‘C’ that obtained by combining amplitude data for each of the 40 test participants. RESULTS: Improvement of the wireless data transmission increased the percentage of analyzable steps from 83.1% measured with a prototype to 96.6% for IngVaL. The linearity comparison showed that the methods A, B, and C were accurate for 2, 15, and 23 participants, respectively. CONCLUSIONS: Increased sensor durability and a higher percentage of analyzed steps indicates that IngVaL is an improvement over the prototype system. The combined strategy of amplitude and step frequency was confirmed as the most accurate method.
