432 research outputs found
An Auto-Calibrating Knee Flexion-Extension Axis Estimator Using Principal Component Analysis with Inertial Sensors
Inertial measurement units (IMUs) have been demonstrated to reliably measure human joint angles—an essential quantity in the study of biomechanics. However, most previous literature proposed IMU-based joint angle measurement systems that required manual alignment or prescribed calibration motions. This paper presents a simple, physically-intuitive method for IMU-based measurement of the knee flexion/extension angle in gait without requiring alignment or discrete calibration, based on computationally-efficient and easy-to-implement Principle Component Analysis (PCA). The method is compared against an optical motion capture knee flexion/extension angle modeled through OpenSim. The method is evaluated using both measured and simulated IMU data in an observational study (n = 15) with an absolute root-mean-square-error (RMSE) of 9.24â and a zero-mean RMSE of 3.49â. Variation in error across subjects was found, made emergent by the larger subject population than previous literature considers. Finally, the paper presents an explanatory model of RMSE on IMU mounting location. The observational data suggest that RMSE of the method is a function of thigh IMU perturbation and axis estimation quality. However, the effect size for these parameters is small in comparison to potential gains from improved IMU orientation estimations. Results also highlight the need to set relevant datums from which to interpret joint angles for both truth references and estimated data.National Science Foundation (U.S.) (GRFP)National Science Foundation (U.S.) (IIS-1453141
Inertial Sensors for Human Motion Analysis: A Comprehensive Review
Inertial motion analysis is having a growing interest during the last decades
due to its advantages over classical optical systems. The technological
solution based on inertial measurement units allows the measurement of
movements in daily living environments, such as in everyday life, which is key
for a realistic assessment and understanding of movements. This is why research
in this field is still developing and different approaches are proposed. This
presents a systematic review of the different proposals for inertial motion
analysis found in the literature. The search strategy has been carried out on
eight different platforms, including journal articles and conference
proceedings, which are written in English and published until August 2022. The
results are analyzed in terms of the publishers, the sensors used, the
applications, the monitored units, the algorithms of use, the participants of
the studies, and the validation systems employed. In addition, we delve deeply
into the machine learning techniques proposed in recent years and in the
approaches to reduce the estimation error. In this way, we show an overview of
the research carried out in this field, going into more detail in recent years,
and providing some research directions for future wor
Novel IMU-based Adaptive Estimator of the Center of Rotation of Joints for Movement Analysis
The location of the center of rotation (COR) of joints is a key parameter in
multiple applications of human motion analysis. The aim of this work was to
propose a novel real-time estimator of the center of fixed joints using an
inertial measurement unit (IMU). Since the distance to this center commonly
varies during the joint motion due to soft tissue artifacts (STA), our approach
is aimed at adapting to these small variations when the COR is fixed. Our
proposal, called ArVEd, to the best of our knowledge, is the first real-time
estimator of the IMU-joint center vector based on one IMU. Previous works are
off-line and require a complete measurement batch to be solved and most of them
are not tested on the real scenario. The algorithm is based on an Extended
Kalman Filter (EKF) that provides an adaptive vector to STA motion variations
at each time instant, without requiring a pre-processing stage to reduce the
level of noise. ArVEd has been tested through different experiments, including
synthetic and real data. The synthetic data are obtained from a simulated
spherical pendulum whose COR is fixed, considering both a constant and a
variable IMU-joint vector, that simulates translational IMU motions due to STA.
The results prove that ArVEd is adapted to obtain a vector per sample with an
accuracy of 6.83.9 on the synthetic data, that means an error lower than
3.5% of the simulated IMU-joint vector. Its accuracy is also tested on the real
scenario estimating the COR of the hip of 5 volunteers using as reference the
results from an optical system. In this case, ArVEd gets an average error of
9.5% of the real vector value. In all the experiments, ArVEd outperforms the
published results of the reference algorithms.Comment: \c{opyright} 2021 IEEE. Personal use of this material is permitted.
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Measurement of Upper Limb Range of Motion Using Wearable Sensors: A Systematic Review.
Background: Wearable sensors are portable measurement tools that are becoming increasingly popular for the measurement of joint angle in the upper limb. With many brands emerging on the market, each with variations in hardware and protocols, evidence to inform selection and application is needed. Therefore, the objectives of this review were related to the use of wearable sensors to calculate upper limb joint angle. We aimed to describe (i) the characteristics of commercial and custom wearable sensors, (ii) the populations for whom researchers have adopted wearable sensors, and (iii) their established psychometric properties. Methods: A systematic review of literature was undertaken using the following data bases: MEDLINE, EMBASE, CINAHL, Web of Science, SPORTDiscus, IEEE, and Scopus. Studies were eligible if they met the following criteria: (i) involved humans and/or robotic devices, (ii) involved the application or simulation of wearable sensors on the upper limb, and (iii) calculated a joint angle. Results: Of 2191 records identified, 66 met the inclusion criteria. Eight studies compared wearable sensors to a robotic device and 22 studies compared to a motion analysis system. Commercial (n = 13) and custom (n = 7) wearable sensors were identified, each with variations in placement, calibration methods, and fusion algorithms, which were demonstrated to influence accuracy. Conclusion: Wearable sensors have potential as viable instruments for measurement of joint angle in the upper limb during active movement. Currently, customised application (i.e. calibration and angle calculation methods) is required to achieve sufficient accuracy (error < 5°). Additional research and standardisation is required to guide clinical application
Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion
Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error)
Using Distributed Wearable Sensors to Measure and Evaluate Human Lower Limb Motions
This paper presents a wearable sensor approach to motion measurements of human lower limbs, in which subjects perform specified walking trials at self-administered speeds so that their level walking and stair ascent capacity can be effectively evaluated. After an initial sensor alignment with the reduced error, quaternion is used to represent 3-D orientation and an optimized gradient descent algorithm is deployed to calculate the quaternion derivative. Sensors on the shank offer additional information to accurately determine the instances of both swing and stance phases. The Denavit-Hartenberg convention is used to set up the kinematic chains when the foot stays stationary on the ground, producing state constraints to minimize the estimation error of knee position. The reliability of this system, from the measurement point of view, has been validated by means of the results obtained from a commercial motion tracking system, namely, Vicon, on healthy subjects. The step size error and the position estimation accuracy change are studied. The experimental results demonstrated that the extensively existed sensor misplacement and sensor drift problems can be well solved. The proposed self-contained and environment-independent system is capable of providing consistent tracking of human lower limbs without significant drift
Custom IMU-Based Wearable System for Robust 2.4 GHz Wireless Human Body Parts Orientation Tracking and 3D Movement Visualization on an Avatar
Recent studies confirm the applicability of Inertial Measurement Unit
(IMU)-based systems for human motion analysis. Notwithstanding, high-end
IMU-based commercial solutions are yet too expensive and complex to democratize
their use among a wide range of potential users. Less featured entry-level
commercial solutions are being introduced in the market, trying to fill this
gap, but still present some limitations that need to be overcome. At the same
time, there is a growing number of scientific papers using not commercial, but
custom do-it-yourself IMU-based systems in medical and sports applications.
Even though these solutions can help to popularize the use of this technology,
they have more limited features and the description on how to design and build
them from scratch is yet too scarce in the literature. The aim of this work is
two-fold: (1) Proving the feasibility of building an affordable custom solution
aimed at simultaneous multiple body parts orientation tracking; while providing
a detailed bottom-up description of the required hardware, tools, and
mathematical operations to estimate and represent 3D movement in real-time. (2)
Showing how the introduction of a custom 2.4 GHz communication protocol
including a channel hopping strategy can address some of the current
communication limitations of entry-level commercial solutions. The proposed
system can be used for wireless real-time human body parts orientation tracking
with up to 10 custom sensors, at least at 50 Hz. In addition, it provides a
more reliable motion data acquisition in Bluetooth and Wi-Fi crowded
environments, where the use of entry-level commercial solutions might be
unfeasible. This system can be used as a groundwork for developing affordable
human motion analysis solutions that do not require an accurate kinematic
analysis.Comment: 25 page
Custom IMU-Based Wearable System for Robust 2.4 GHz Wireless Human Body Parts Orientation Tracking and 3D Movement Visualization on an Avatar
Recent studies confirm the applicability of Inertial Measurement Unit (IMU)-based systems for human motion analysis. Notwithstanding, high-end IMU-based commercial solutions are yet too expensive and complex to democratize their use among a wide range of potential users. Less featured entry-level commercial solutions are being introduced in the market, trying to fill this gap, but still present some limitations that need to be overcome. At the same time, there is a growing number of scientific papers using not commercial, but custom do-it-yourself IMU-based systems in medical and sports applications. Even though these solutions can help to popularize the use of this technology, they have more limited features and the description on how to design and build them from scratch is yet too scarce in the literature. The aim of this work is two-fold: (1) Proving the feasibility of building an affordable custom solution aimed at simultaneous multiple body parts orientation tracking; while providing a detailed bottom-up description of the required hardware, tools, and mathematical operations to estimate and represent 3D movement in real-time. (2) Showing how the introduction of a custom 2.4 GHz communication protocol including a channel hopping strategy can address some of the current communication limitations of entry-level commercial solutions. The proposed system can be used for wireless real-time human body parts orientation tracking with up to 10 custom sensors, at least at 50 Hz. In addition, it provides a more reliable motion data acquisition in Bluetooth and Wi-Fi crowded environments, where the use of entry-level commercial solutions might be unfeasible. This system can be used as a groundwork for developing affordable human motion analysis solutions that do not require an accurate kinematic analysis.This research has been partially funded by a research contract with IVECO Spain SL and by the Department of Employment and Industry of Castilla y LeĂłn (Spain), under research project ErgoTwyn (INVESTUN/21/VA/0003)
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