Abstract
BackgroundGait analysis plays an important role in the diagnosis and management of patients with movement disorders but it is usually performed within a laboratory. Recently interest has shifted towards the possibility of conducting gait assessments in everyday environments thus facilitating long-term monitoring. This is possible by using wearable technologies rather than laboratory based equipment. Research questionThis study aims to validate a novel wearable sensor system’s ability to measure peak knee sagittal angles during gait. MethodsThe proposed system comprises a flexible conductive polymer unit interfaced with a wireless acquisition node attached over the knee on a pair of leggings. Sixteen healthy volunteers participated to two gait assessments on separate occasions. Data was simultaneously collected from the novel sensor and a gold standard 10 camera motion capture system. The relationship between sensor signal and reference knee flexion angles was defined for each subject to allow the transformation of sensor voltage outputs to angular measures (degrees). The knee peak flexion angle from the sensor and reference system were compared by means of root mean square error (RMSE), absolute error, Bland-Altman plots and intra-class correlation coefficients (ICCs) to assess test-retest reliability. ResultsComparisons of knee peak flexion angles calculated from the sensor and gold standard yielded an absolute error of 0.35(±2.9°) and RMSE of 1.2(±0.4)°. Good agreement was found between the two systems with the majority of data lying within the limits of agreement. The sensor demonstrated high test-retest reliability (ICCs>0.8). SignificanceThese results show the ability of the sensor to monitor knee peak sagittal angles with small margins of error and in agreement with the gold standard system. The sensor has potential to be used in clinical settings as a discreet, unobtrusive wearable device allowing for long-term gait analysis.
Highlights
The use of technology for gait analysis has led to improvements in gait assessment over standard observational analysis as it provides quantitative data on the gait cycle by objective measurement of body kinematics and kinetics [1]
A mean root mean square error (RMSE) of 1.2( ± 0.4)° was found for both tests
Knee peak flexion angles could be calculated from the sensor signal output by applying equations derived from linear fittings of motion capture system (MCS) angles and sensor outputs for each participant
Summary
The use of technology for gait analysis has led to improvements in gait assessment over standard observational analysis as it provides quantitative data on the gait cycle by objective measurement of body kinematics and kinetics [1]. With the introduction and recent development of wearable technologies, there is a growing interest in being able to transfer the analysis, usually performed in the laboratory, to real-life environments permitting long-term monitoring [2]. Interest has shifted towards the possibility of conducting gait assessments in everyday environments facilitating long-term monitoring. This is possible by using wearable technologies rather than laboratory based equipment. Research question: This study aims to validate a novel wearable sensor system’s ability to measure peak knee sagittal angles during gait. Significance: These results show the ability of the sensor to monitor knee peak sagittal angles with small margins of error and in agreement with the gold standard system. The sensor has potential to be used in clinical settings as a discreet, unobtrusive wearable device allowing for long-term gait analysis
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