scholarly journals Gait Variability Using Waist- and Ankle-Worn Inertial Measurement Units in Healthy Older Adults

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2858 ◽  
Author(s):  
Timo Rantalainen ◽  
Laura Karavirta ◽  
Henrikki Pirkola ◽  
Taina Rantanen ◽  
Vesa Linnamo

Gait variability observed in step duration is predictive of impending adverse health outcomes among apparently healthy older adults and could potentially be evaluated using wearable sensors (inertial measurement units, IMU). The purpose of the present study was to establish the reliability and concurrent validity of gait variability and complexity evaluated with a waist and an ankle-worn IMU. Seventeen women (age 74.8 (SD 44) years) and 10 men (73.7 (4.1) years) attended two laboratory measurement sessions a week apart. Their stride duration variability was concurrently evaluated based on a continuous 3 min walk using a force plate and a waist- and an ankle-worn IMU. Their gait complexity (multiscale sample entropy) was evaluated from the waist-worn IMU. The force plate indicated excellent stride duration variability reliability (intra-class correlation coefficient, ICC = 0.90), whereas fair to good reliability (ICC = 0.47 to 0.66) was observed from the IMUs. The IMUs exhibited poor to excellent concurrent validity in stride duration variability compared to the force plate (ICC = 0.22 to 0.93). A good to excellent reliability was observed for gait complexity in most coarseness scales (ICC = 0.60 to 0.82). A reasonable congruence with the force plate-measured stride duration variability was observed on many coarseness scales (correlation coefficient = 0.38 to 0.83). In conclusion, waist-worn IMU entropy estimates may provide a feasible indicator of gait variability among community-dwelling ambulatory older adults.

2015 ◽  
Vol 23 (1) ◽  
pp. 18-23 ◽  
Author(s):  
M. Monda ◽  
A. Goldberg ◽  
P. Smitham ◽  
M. Thornton ◽  
I. McCarthy

To study mobility in older populations it can be advantageous to use portable gait analysis systems, such as inertial measurement units (IMUs), which can be used in the community. To define a normal range, 136 active subjects were recruited with an age range of 18 to 97. Four IMUs were attached to the subjects, one on each thigh and shank. Subjects were asked to walk 10 m at their own self-selected speed. The ranges of motion of thigh, shank, and knee in both swing and stance phase were calculated, in addition to stride duration. Thigh, shank, and knee range of movement in swing and stance were significantly different only in the > 80 age group. Regressions of angle against age showed a cubic relationship. Stride duration showed a weak linear relationship with age, increasing by approximately 0.1% per year.


Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2983
Author(s):  
Marie Sapone ◽  
Pauline Martin ◽  
Khalil Ben Mansour ◽  
Henry Château ◽  
Frédéric Marin

The development of on-board sensors, such as inertial measurement units (IMU), has made it possible to develop new methods for analyzing horse locomotion to detect lameness. The detection of spatiotemporal events is one of the keystones in the analysis of horse locomotion. This study assesses the performance of four methods for detecting Foot on and Foot off events. They were developed from an IMU positioned on the canon bone of eight horses during trotting recording on a treadmill and compared to a standard gold method based on motion capture. These methods are based on accelerometer and gyroscope data and use either thresholding or wavelets to detect stride events. The two methods developed from gyroscopic data showed more precision than those developed from accelerometric data with a bias less than 0.6% of stride duration for Foot on and 0.1% of stride duration for Foot off. The gyroscope is less impacted by the different patterns of strides, specific to each horse. To conclude, methods using the gyroscope present the potential of further developments to investigate the effects of different gait paces and ground types in the analysis of horse locomotion.


2016 ◽  
Vol 37 (3) ◽  
pp. 442-461 ◽  
Author(s):  
Fouaz S Ayachi ◽  
Hung P Nguyen ◽  
Catherine Lavigne-Pelletier ◽  
Etienne Goubault ◽  
Patrick Boissy ◽  
...  

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 173 ◽  
Author(s):  
Nicolas Valencia-Jimenez ◽  
Arnaldo Leal-Junior ◽  
Leticia Avellar ◽  
Laura Vargas-Valencia ◽  
Pablo Caicedo-Rodríguez ◽  
...  

This paper presents a comparison between a multiple red green blue-depth (RGB-D) vision system, an intensity variation-based polymer optical fiber (POF) sensor, and inertial measurement units (IMUs) for human joint angle estimation and movement analysis. This systematic comparison aims to study the trade-off between the non-invasive feature of a vision system and its accuracy with wearable technologies for joint angle measurements. The multiple RGB-D vision system is composed of two camera-based sensors, in which a sensor fusion algorithm is employed to mitigate occlusion and out-range issues commonly reported in such systems. Two wearable sensors were employed for the comparison of angle estimation: (i) a POF curvature sensor to measure 1-DOF angle; and (ii) a commercially available IMUs MTw Awinda from Xsens. A protocol to evaluate elbow joints of 11 healthy volunteers was implemented and the comparison of the three systems was presented using the correlation coefficient and the root mean squared error (RMSE). Moreover, a novel approach for angle correction of markerless camera-based systems is proposed here to minimize the errors on the sagittal plane. Results show a correlation coefficient up to 0.99 between the sensors with a RMSE of 4.90 ∘ , which represents a two-fold reduction when compared with the uncompensated results (10.42 ∘ ). Thus, the RGB-D system with the proposed technique is an attractive non-invasive and low-cost option for joint angle assessment. The authors envisage the proposed vision system as a valuable tool for the development of game-based interactive environments and for assistance of healthcare professionals on the generation of functional parameters during motion analysis in physical training and therapy.


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