scholarly journals Estimation of the External Knee Adduction Moment during Gait Using an Inertial Measurement Unit in Patients with Knee Osteoarthritis

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1418
Author(s):  
Yu Iwama ◽  
Kengo Harato ◽  
Shu Kobayashi ◽  
Yasuo Niki ◽  
Naomichi Ogihara ◽  
...  
Keyword(s):  
Knee Osteoarthritis ◽  
Motion Capture ◽  
Inertial Measurement Unit ◽  
Knee Adduction Moment ◽  
Measurement Unit ◽  
Motion Capture System ◽  
Medial Knee ◽  
Inertial Measurement ◽  
Knee Oa ◽  
External Knee Adduction Moment

Although the external knee adduction moment (KAM) during gait was shown to be a quantitative parameter of medial knee osteoarthritis (OA), it requires expensive equipment and a dedicated large space to measure. Therefore, it becomes a major reason to limit KAM measurement in a clinical environment. The purpose of this study was to estimate KAM using a single inertial measurement unit (IMU) during gait in patients with knee OA. A total of 22 medial knee OA patients (44 knee joints) performed conventional gait analysis using three-dimensional (3D) motion capture system. At the same time, we attached commercial IMUs to six body segments (sternum, pelvis, both thighs, and both shanks), and IMU signals during gait were recorded synchronized with the motion capture system. The peak-to-peak difference of acceleration in the lateral/medial axis immediately after heel contact was defined as the thrust acceleration (TA). We hypothesized that TA would represent the lateral thrust of the knee during the stance phase and correlate with the first peak of KAM. The relationship between the peak KAM and TA of pelvis (R = 0.52, p < 0.001), shanks (R = 0.57, p < 0.001) and thighs (R = 0.49, p = 0.001) showed a significant correlation. The root mean square error (RMSE) of linear regression models of pelvis, shanks, and thighs to estimate KAM were 0.082, 0.079, and 0.084 Nm/(kg·m), respectively. Our newly established parameter TA showed a moderate correlation with conventional KAM. The current study confirmed our hypothesis that a single IMU would predict conventional KAM during gait. Since KAM is known as an indicator for prognosis and severity of knee OA, this new parameter has the potential to become an accessible predictor for medial knee OA instead of KAM.

scholarly journals Quaternion-Based Local Frame Alignment between an Inertial Measurement Unit and a Motion Capture System

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 4003 ◽  
Author(s):  
Jung Keun Lee ◽  
Woo Chang Jung
Keyword(s):  
Angular Velocity ◽  
Motion Capture ◽  
Inertial Measurement Unit ◽  
Least Squares Method ◽  
Measurement Unit ◽  
Motion Capture System ◽  
Inertial Measurement ◽  
Local Frame ◽  
Velocity Transformation ◽  
Frame Alignment

Local frame alignment between an inertial measurement unit (IMU) system and an optical motion capture system (MCS) is necessary to combine the two systems for motion analysis and to validate the accuracy of IMU-based motion data by using references obtained through the MCS. In this study, we propose a new quaternion-based local frame alignment method where equations of angular velocity transformation are used to determine the frame alignment orientation in the form of quaternion. The performance of the proposed method was compared with those of three other methods by using data with different angular velocities, noises, and alignment orientations. Furthermore, the effects of the following three factors on the estimation performance were investigated for the first time: (i) transformation concept, i.e., angular velocity transformation vs. angle transformation; (ii) orientation representations, i.e., quaternion vs. direction cosine matrix (DCM); and (iii) applied solvers, i.e., nonlinear least squares method vs. least squares method through pseudoinverse. Within our limited test data, we obtained the following results: (i) the methods using angular velocity transformation were better than the method using angle transformation; (ii) the quaternion is more suitable than the DCM; and (iii) the applied solvers were not critical in general. The proposed method performed the best among the four methods. We surmise that the fewer number of components and constraints of the quaternion in the proposed method compared to the number of components and constraints of the DCM-based methods may result in better accuracy. Owing to the high accuracy and easy setup, the proposed method can be effectively used for local frame alignment between an IMU and a motion capture system.

scholarly journals Comparison of a New Inertial Sensor Based System with an Optoelectronic Motion Capture System for Motion Analysis of Healthy Human Wrist Joints

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5297 ◽  
Author(s):  
Michael Alexander Wirth ◽  
Gabriella Fischer ◽  
Jorge Verdú ◽  
Lisa Reissner ◽  
Simone Balocco ◽  
...  
Keyword(s):  
Range Of Motion ◽  
Motion Capture ◽  
Inertial Measurement Unit ◽  
Absolute Difference ◽  
Measurement Unit ◽  
Good Precision ◽  
Motion Capture System ◽  
Ulnar Deviation ◽  
Inertial Measurement ◽  
Flexion Extension

This study aims to compare a new inertial measurement unit based system with the highly accurate but complex laboratory gold standard, an optoelectronic motion capture system. Inertial measurement units are sensors based on accelerometers, gyroscopes, and/or magnetometers. Ten healthy subjects were recorded while performing flexion-extension and radial-ulnar deviation movements of their right wrist using inertial sensors and skin markers. Maximum range of motion during these trials and mean absolute difference between the systems were calculated. A difference of 10° ± 5° for flexion-extension and 2° ± 1° for radial-ulnar deviation was found between the two systems with absolute range of motion values of 126° and 50° in the respective axes. A Wilcoxon rank sum test resulted in a no statistical differences between the systems with p-values of 0.24 and 0.62. The observed results are even more precise than reports from previous studies, where differences between 14° and 27° for flexion-extension and differences between 6° and 17° for radial-ulnar deviation were found. Effortless and fast applicability, good precision, and low inter-observer variability make inertial measurement unit based systems applicable to clinical settings.

scholarly journals Kajian Inertial Measurement Unit Berbasis Arduino Untuk Dokumentasi Digital Motion Capture Tarian Tradisional

2017 ◽  
Vol 2 (2) ◽  
pp. 251
Author(s):  
FX. Satriyo Dwi Nugroho
Keyword(s):  
Motion Capture ◽  
Inertial Measurement Unit ◽  
Rotation Axis ◽  
Three Dimensions ◽  
Measurement Unit ◽  
Motion Capture Data ◽  
Inertial Measurement ◽  
Digital Heritage ◽  
Traditional Dance ◽  
Digital Documentation

Visual digital documentation of traditional dance in Indonesia is still limited to photographs and videos recording. Motion capture technology has the potential to add more depth documenting traditional dances. This technology maps the position of the model (in this case the human body) and its motion in three dimensions. There are two popular ways in recording motion capture, using Vision Based Camera and Inertial measurement unit. Inertial Measurement Unit works by combining accelerometer and gyroscope to detect changes in the rotation axis relative lateral and angular. Those changes will be interpreted Arduino micro-controller platform as functions of motions that recorded as a motion capture data. Motion capture data that was obtained from traditional dance in Indonesia can be applied for many things such as education, standardization, documentation, and preservation of cultural assetsKeywords: digital documentatuion, motion capture, inertia measurement unit, angular relative, digital heritage. Abstrak Dokumentasi digital secara visual untuk tari tradisional di Indonesia masih terbatas pada perekaman secara fotografis dan videografis. Teknologi motion capture memiliki potensi untuk menambah kekayaan dokumentasi untuk tari tradisional. Teknologi ini memetakan posisi model (dalam hal ini tubuh manusia) dan pergerakannya secara 3 dimensi. Ada dua cara yang populer dalam perekaman motion capture, menggunakan Vision Based Camera dan Inertial measurement unit. Inertial Measurement Unit bekerja dengan menggabungkan accelerometer dan gyroscope untuk mendeteksi perubahan sumbu rotasi secara lateral dan angular relative. Perubahan ini yang oleh platform mikro-kontroler Arduino akan diterjemahkan sebagai fungsi gerakan yang nantinya akan direkam sebagai data motion capture. Data dokumentasi digital motion capture yang didapat dari perekaman gerak tari tradisional di Indonesia dapat diaplikasikan untuk banyak hal seperti edukasi, standarisasi, pembuatan animasi, game, dan pelestarian aset budaya. Kata kunci: dokumentasi digital, motion capture, inertia measurement unit, angular relative, pelestarian asset budaya

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