Flexible and attachable inertial measurement unit (IMU)-based motion capture instrumentation for the characterization of hand kinematics: A pilot study

2020 ◽  
pp. 1-21
Author(s):  
Bingcheng Hu ◽  
Tian Ding ◽  
Yuxin Peng ◽  
Li Liu ◽  
Xu Wen
Keyword(s):  
Pilot Study ◽  
Motion Capture ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Hand Kinematics

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

scholarly journals Comparison of Trotting Stance Detection Methods from an Inertial Measurement Unit Mounted on the Horse’s Limb

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2983
Author(s):  
Marie Sapone ◽  
Pauline Martin ◽  
Khalil Ben Mansour ◽  
Henry Château ◽  
Frédéric Marin
Keyword(s):  
Motion Capture ◽  
Inertial Measurement Unit ◽  
Detection Methods ◽  
Measurement Unit ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
New Methods ◽  
Measurement Units ◽  
Ground Types ◽  
Stride Duration

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.

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.

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