Validation of a portable system for spatial-temporal gait parameters based on a single inertial measurement unit and a mobile application

Abstract

There is a lack of commercially available low-cost technologies to assess gait clinically in non-controlled environments. As a consequence of this, there has been poor massification of motion measurement technologies that are both objective and reliable in nature. Advances about the study of gait and its interpretation in recent years using inertial sensors have allowed proposing acceptable alternatives for the development of portable and low-cost systems that contribute to people’s health in places and institutions that cannot acquire or maintain the operation of commercially available systems. A system based on a custom single Inertial Measurement Unit and a mobile application is proposed. Thus, an investigation is carried out using methodologies and algorithms found in the literature in order to get the main gait events and the spatial-temporal gait parameters. Twenty healthy Chilean subjects were assessed using a motion capture system simultaneously with the proposed tool. The results show that it is possible to estimate temporal gait parameters with slight differences respect gold--standard. We reach maximum mean differences of -2.35±5.02[step/min] for cadence, 0.03±0.04[sec] for stride time,0.02±0.03[sec] for step time, ±0.02[sec] for a single support time, 0.01±0.02[sec] for double support time and 0.01±0.03[m] for step length. As a result of experimental findings, we propose a new technological tool that can perform gait analysis. Our proposed system is user-friendly, low-cost, and portable. Therefore, we suggest that it could be an attractive technological tool that healthcare professionals could harness to objectively measure gait in environments that are either within the community or controlled. We also suggest that the tool could be used in countries where advanced clinical tools cannot be acquired. Therefore, we propose in this paper that our system is an attractive, alternative system that can be used for gait analysis by health professionals worldwide.

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“…This may also advance the reproducibility of DFA AP up to an acceptable level. Besides being reliable, highly economical, and practical, IMU signals have frequently been connected to smartphone applications (e.g., Aqueveque et al, 2020 ). Moving forward, such applications could open new possibilities for enabling real-time feedback in self-organization routines such as Newell’s Constraints Led Approaches.…”

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“…The mobile app incorporates two algorithms developed and validated previously by the research team of this work. The first assess the risk of falls through the segmentation of the instrumented Timed Up & Go test (iTUG) [26], and the second is used for the analysis of gait through the instrumented 10 m walking test (iT10M) [27] (see Figure 4). The mobile app communicates with an application programming interface (API) to manage the database where the user's pre-selected data are stored.…”

“…The instrumentation of this test allows estimating gait parameters with a single sensor located on the lower-back of the patient using a wearable alternative. The algorithm for gait analysis used and validated by the research team [27] allows processing the tri-axial accelerometry signals from the lower back. During the execution of the gait test, these data permit identifying the events of initial contact and final contact of each foot and, in this way, identifying the main gait events.…”

“…To verify the practical effectiveness and efficiency of our methodology, we also developed a home-care-oriented movement analysis system based on a wearable magnetoinertial measurement unit (MIMU). Technically, the MIMU sends raw data (tri-axial acceleration, tri-axial angular velocity, and tri-dimensional orientations) to a mobile platform to calculate clinical assessment scales for analysing the risk of falls and the gait quality [26,27]. The advances in movement analysis algorithms and device miniaturization make this system a low-cost and easy-to-use alternative to those high-technological systems of specialised laboratories for the bio-mechanical analysis of movement [28].…”

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“…These technologies were all developmental, apart from the use of Shimmer IMUs(Oubre et al 2020). This indicates a eld of research that is cumulatively gaining interest, however, requires increased complexities of computational predictive modelling to produce joint angle data due The variability of IMU data collection methods and lack of consensus in terms of standard measures, IMU positioning, or approach offers researchers exibility for application however it decreases the ability to compare and utilise shared data and results(Aqueveque et al 2020). Aqueveque provided recommendations for IMU data collection methods for SPT parameters towards the standardisation of IMU data collection methods, however, further pragmatic guidelines using validated methods are required to aid future remote gait assessment where environmental unknowns will complicate data interpretation(Celik et al 2021).…”