scholarly journals Accuracy Verification of Spatio-Temporal and Kinematic Parameters for Gait Using Inertial Measurement Unit System

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1343 ◽  
Author(s):  
Sang Seok Yeo ◽  
Ga Young Park

Inertial measurement unit systems are wearable sensors that can measure the movement of a human in real-time with relatively little space and high portability. The purpose of this study was to investigate the accuracy of the inertial measurement unit (IMU) system for gait analysis by comparing it with measurements obtained using an optical motion capture (OMC) system. To compare the accuracies of these two different motion capture systems, the Spatio-temporal and kinematic parameters were measured in young adults during normal walking. Thirty healthy participants participated in the study. Data were collected while walking 5 strides on a 7 m walkway at a self-selected speed. Results of gait analysis showed that the Spatio-temporal (stride time, stride length, cadence, step length) and kinematic (knee joint peak to peak of movement) parameters were not significantly different in the participant. Spatio-temporal and kinematic parameters of the two systems were compared using the Bland–Altman method. The results obtained showed that the measurements of Spatio-temporal and kinematic parameters of gait by the two systems were similar, which suggested that IMU and OMC systems could be used interchangeably for gait measurements. Therefore, gait analysis performed using the wearable IMU system might efficiently provide gait measurements and enable accurate analysis.

2018 ◽  
Vol 42 (6) ◽  
pp. 872-883 ◽  
Author(s):  
Young-Shin Cho ◽  
Seong-Ho Jang ◽  
Jae-Sung Cho ◽  
Mi-Jung Kim ◽  
Hyeok Dong Lee ◽  
...  

2018 ◽  
Vol 64 (2) ◽  
pp. 240-248 ◽  
Author(s):  
Tong-Hun Hwang ◽  
Julia Reh ◽  
Alfred O. Effenberg ◽  
Holger Blume

2020 ◽  
Vol 44 (1) ◽  
pp. 48-57
Author(s):  
Junhee Lee ◽  
Chang Hoon Bae ◽  
Aeri Jang ◽  
Seoyon Yang ◽  
Hasuk Bae

Objective To evaluate the gait pattern of patients with gait disturbances without consideration of defilades due to assistive devices. This study focuses on gait analysis using the inertial measurement unit (IMU) system, which can also be used to determine the most appropriate assistive device for patients with gait disturbances.Methods Records of 18 disabled patients who visited the Department of Rehabilitation from May 2018 to June 2018 were selected. Patients’ gait patterns were analyzed using the IMU system with different assistive devices to determine the most appropriate device depending on the patient’s condition. Evaluation was performed using two or more devices, and the appropriate device was selected by comparing the 14 parameters of gait evaluation. The device showing measurements nearer or the nearest to the normative value was selected for rehabilitation.Results The result of the gait evaluation in all 18 patients was analyzed using the IMU system. According to the records, the patients were evaluated using various assistive devices without consideration of defilades. Moreover, this gait analysis was effective in determining the most appropriate device for each patient. Increased gait cycle time and swing phase and decreased stance phase were observed in devices requiring significant assistance.Conclusion The IMU-based gait analysis system is beneficial in evaluating gait in clinical fields. Specifically, it is useful in evaluating patients with gait disturbances who require assistive devices. Furthermore, it allows the establishment of an evidence-based decision for the most appropriate assistive walking devices for patients with gait disturbances.


2017 ◽  
Vol 2 (2) ◽  
pp. 251
Author(s):  
FX. Satriyo Dwi Nugroho

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


2021 ◽  
Vol 10 (1) ◽  
pp. 29
Author(s):  
Niharika Gogoi ◽  
Zixuan Yu ◽  
Yichun Qin ◽  
Jens Kirchner ◽  
Georg Fischer

Human gait analysis is a growing field of research interest in medical treatment, sports training and structural health monitoring. In our study, we propose a low-cost insole design with wearable sensors based on piezoelectric discs (PZT) and an inertial measurement unit (IMU) to acquire the human gait. The sensors are placed at three points of a shoe sole: toe, metatarsal and heel. The human gait obtained from such an insole layout is significantly affected by plantar pressure distribution and alignment of the feet. The PZT sensors give an insight into the pressure map under the feet, and the IMUs record projection and orientation of the feet.


Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2983
Author(s):  
Marie Sapone ◽  
Pauline Martin ◽  
Khalil Ben Mansour ◽  
Henry Château ◽  
Frédéric Marin

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.


Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 4003 ◽  
Author(s):  
Jung Keun Lee ◽  
Woo Chang Jung

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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