scholarly journals Wireless Epidermal Six-Axis Inertial Measurement Units for Real-Time Joint Angle Estimation

2020 ◽  
Vol 10 (7) ◽  
pp. 2240 ◽  
Author(s):  
Jae Keun Lee ◽  
Seung Ju Han ◽  
Kangil Kim ◽  
Yoon Hyuk Kim ◽  
Sangmin Lee
Keyword(s):  
Real Time ◽  
Human Body ◽  
Joint Angle ◽  
The Body ◽  
Measurement Unit ◽  
Processing Unit ◽  
Solder Paste ◽  
Angle Estimation ◽  
Patch Type ◽  
Inertial Measurement

Technological advances in wireless communications, miniaturized sensors, and low-power electronics have made it possible to implement integrated wireless body area networks (WBANs). These developments enable the applications of wireless wearable systems for diagnosis, health monitoring, rehabilitation, and dependency care. Across the current range of commercial wearable devices, the products are not firmly fixed to the human body. To minimize data error caused by movement of the human body and to achieve accurate measurements, it is essential to bring the wearable device close to the skin. This paper presents the implementation of a patch-type, six-axis inertial measurement unit (IMU) with wireless communication technology. The device comprises hard-electronic components on a stretchable elastic substrate for application in epidermal electronics, to collect precise data from the human body. Instead of the commonly used cleanroom processes of implementing devices on a stretchable substrate, a simple and inexpensive “cut-solder-paste” method is adopted to fabricate complex, convoluted interconnections. Thus, the signal distortions in the proposed device can be minimized during various physical activities and skin deformations when used in gait analysis. The inertial sensor data measured from the motion of the body can be sent in real-time via Bluetooth to any processing unit enabled with such a widespread standard wireless interface. For performance evaluation, the implemented device is mounted on a rotation plate in order to compare performance with the conventional product. In addition, an experiment on joint angle estimation is performed by attaching the device to an actual human body. The preliminary results of the device indicate the potential to monitor people in remote settings for applications in mobile health, human-computer interfaces (HCIs), and wearable robots.

scholarly journals Stretchable, Patch-Type, Wireless, 6-axis Inertial Measurement Unit for Mobile Health Monitoring

2020 ◽  
Vol 14 ◽  
pp. 16-21 ◽  
Author(s):  
Jae Keun Lee ◽  
Kangil Kim ◽  
Sangmin Lee
Keyword(s):  
Mobile Health ◽  
Human Body ◽  
Health Monitoring ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Biometric Data ◽  
Patch Type ◽  
Inertial Measurement ◽  
Dependency Care ◽  
Mobile Health Monitoring

Wearable devices which measure and transfer signals from the human body can provide useful biometric data for various biomedical applications. In this paper, we present an implementation of the advanced Inertial Measurement Unit (IMU) with wireless communication technology for mobile health monitoring. The device consists of rigid silicon-based components on a flexible/stretchable substrate for applications in epidermal electronic devices to collect precise data from the human body. Using the Bluetooth Low Energy (BLE) System-on-a-chip (SoC), the device can be miniaturized and portable, and the collected data can be processed with low power consumption. The dimensions of the implemented system are approximately 40 mm × 40 mm × 100 mm. Also, the device can be attached closely to human skin, which results in minimized signal distortion due to body movements or skin deformations. In order to achieve device flexibility and stretch ability, the interconnection wires are designed as serpentine-shaped structures on a stretchable substrate. The previously reported “cut-and-paste” method is utilized to fabricate the device that produces complex, twisty interconnections with thin metal sheets. The implemented patch-type, wireless, 6-axis IMU is expected to have potential in various applications, such as health monitoring, dependency care, and daily lifelogging.

scholarly journals Investigation on Wireless Link for Medical Telemetry Including Impedance Matching of Implanted Antennas

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1431
Author(s):  
Ilkyu Kim ◽  
Sun-Gyu Lee ◽  
Yong-Hyun Nam ◽  
Jeong-Hae Lee
Keyword(s):  
Real Time ◽  
Human Body ◽  
Near Field ◽  
Impedance Matching ◽  
The Body ◽  
Field Pattern ◽  
Communication Link ◽  
Far Field ◽  
Antenna Coupling ◽  
Medical Telemetry

The development of biomedical devices benefits patients by offering real-time healthcare. In particular, pacemakers have gained a great deal of attention because they offer opportunities for monitoring the patient’s vitals and biological statics in real time. One of the important factors in realizing real-time body-centric sensing is to establish a robust wireless communication link among the medical devices. In this paper, radio transmission and the optimal characteristics for impedance matching the medical telemetry of an implant are investigated. For radio transmission, an integral coupling formula based on 3D vector far-field patterns was firstly applied to compute the antenna coupling between two antennas placed inside and outside of the body. The formula provides the capability for computing the antenna coupling in the near-field and far-field region. In order to include the effects of human implantation, the far-field pattern was characterized taking into account a sphere enclosing an antenna made of human tissue. Furthermore, the characteristics of impedance matching inside the human body were studied by means of inherent wave impedances of electrical and magnetic dipoles. Here, we demonstrate that the implantation of a magnetic dipole is advantageous because it provides similar impedance characteristics to those of the human body.

scholarly journals Evaluating the use of machine learning in the assessment of joint angle using a single inertial sensor

2019 ◽  
Vol 6 ◽  
pp. 205566831986854 ◽  
Author(s):  
Rob Argent ◽  
Sean Drummond ◽  
Alexandria Remus ◽  
Martin O’Reilly ◽  
Brian Caulfield
Keyword(s):  
Machine Learning ◽  
Knee Joint ◽  
Inertial Measurement Unit ◽  
Joint Angle ◽  
Machine Learning Algorithms ◽  
Measurement Unit ◽  
Reference Standard ◽  
Inertial Measurement ◽  
Knee Joint Angle ◽  
Single Sensor

Introduction Joint angle measurement is an important objective marker in rehabilitation. Inertial measurement units may provide an accurate and reliable method of joint angle assessment. The objective of this study was to assess whether a single sensor with the application of machine learning algorithms could accurately measure hip and knee joint angle, and investigate the effect of inertial measurement unit orientation algorithms and person-specific variables on accuracy. Methods Fourteen healthy participants completed eight rehabilitation exercises with kinematic data captured by a 3D motion capture system, used as the reference standard, and a wearable inertial measurement unit. Joint angle was calculated from the single inertial measurement unit using four machine learning models, and was compared to the reference standard to evaluate accuracy. Results Average root-mean-squared error for the best performing algorithms across all exercises was 4.81° (SD = 1.89). The use of an inertial measurement unit orientation algorithm as a pre-processing step improved accuracy; however, the addition of person-specific variables increased error with average RMSE 4.99° (SD = 1.83°). Conclusions Hip and knee joint angle can be measured with a good degree of accuracy from a single inertial measurement unit using machine learning. This offers the ability to monitor and record dynamic joint angle with a single sensor outside of the clinic.

A Real-Time Photogrammetric System for Acquisition and Monitoring of Three-Dimensional Human Body Kinematics

2021 ◽  
Vol 87 (5) ◽  
pp. 363-373
Author(s):  
Long Chen ◽  
Bo Wu ◽  
Yao Zhao ◽  
Yuan Li
Keyword(s):  
Real Time ◽  
Human Body ◽  
Graphics Processing Unit ◽  
Three Dimensional ◽  
Stereo Pair ◽  
Processing Unit ◽  
Detection Distance ◽  
Human Kinematics ◽  
Graphics Processing ◽  
Time Acquisition

Real-time acquisition and analysis of three-dimensional (3D) human body kinematics are essential in many applications. In this paper, we present a real-time photogrammetric system consisting of a stereo pair of red-green-blue (RGB) cameras. The system incorporates a multi-threaded and graphics processing unit (GPU)-accelerated solution for real-time extraction of 3D human kinematics. A deep learning approach is adopted to automatically extract two-dimensional (2D) human body features, which are then converted to 3D features based on photogrammetric processing, including dense image matching and triangulation. The multi-threading scheme and GPU-acceleration enable real-time acquisition and monitoring of 3D human body kinematics. Experimental analysis verified that the system processing rate reached ∼18 frames per second. The effective detection distance reached 15 m, with a geometric accuracy of better than 1% of the distance within a range of 12 m. The real-time measurement accuracy for human body kinematics ranged from 0.8% to 7.5%. The results suggest that the proposed system is capable of real-time acquisition and monitoring of 3D human kinematics with favorable performance, showing great potential for various applications.

scholarly journals Real-Time Gait Analysis Using a Single Head-Worn Inertial Measurement Unit

2018 ◽  
Vol 64 (2) ◽  
pp. 240-248 ◽  
Author(s):  
Tong-Hun Hwang ◽  
Julia Reh ◽  
Alfred O. Effenberg ◽  
Holger Blume
Keyword(s):  
Gait Analysis ◽  
Real Time ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Inertial Measurement

New method to evaluate three-dimensional push-off angle during short-track speed skating using wearable inertial measurement unit sensors

2019 ◽  
Vol 233 (4) ◽  
pp. 476-480 ◽  
Author(s):  
Kyungsoo Kim ◽  
Jun Seok Kim ◽  
Tserenchimed Purevsuren ◽  
Batbayar Khuyagbaatar ◽  
SuKyoung Lee ◽  
...  
Keyword(s):  
Motion Analysis ◽  
Inertial Measurement Unit ◽  
High Speed ◽  
Three Dimensional ◽  
Analysis Data ◽  
New Method ◽  
Measurement Unit ◽  
Angle Estimation ◽  
Inertial Measurement ◽  
Speed Skating

The push-off mechanism to generate forward movement in skating has been analyzed by using high-speed cameras and specially designed skates because it is closely related to skater performance. However, using high-speed cameras for such an investigation, it is hard to measure the three-dimensional push-off force, and a skate with strain gauges is difficult to implement in the real competitions. In this study, we provided a new method to evaluate the three-dimensional push-off angle in short-track speed skating based on motion analysis using a wearable motion analysis system with inertial measurement unit sensors to avoid using a special skate or specific equipment insert into the skate for measurement of push-off force. The estimated push-off angle based on motion analysis data was very close to that based on push-off force with a small root mean square difference less than 6% when using the lateral marker in the left leg and the medial marker in the right leg regardless of skating phase. These results indicated that the push-off angle estimation based on motion analysis data using a wearable motion capture system of inertial measurement unit sensors could be acceptable for realistic situations. The proposed method was shown to be feasible during short-track speed skating. This study is meaningful because it can provide a more acceptable push-off angle estimation in real competitive situations.

Development and Implementation of a Novel Digital Shot Sensor System

2013 ◽  
Vol 364 ◽  
pp. 228-232
Author(s):  
Wei Tian Wang ◽  
Quan Jun Song ◽  
Yu Man Nie ◽  
Bu Yun Wang ◽  
Hong Yu Ren ◽  
...  
Keyword(s):  
Real Time ◽  
Information Acquisition ◽  
Inertial Measurement Unit ◽  
Degrees Of Freedom ◽  
Sensor System ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Kinetic Information ◽  
Shot Put

Kinetic information acquisition of shot throwing is significant for the train of shot put athletes. This paper presents a novel sensor system based on a 9 degrees of freedom inertial measurement unit, which provides attitude information of shot throwing in real time. The sensor system is designed with modularized structure and installed in the digital shot which has almost the same size and weight as the standard shot for females. A multi-target and multi-parameter information acquisition platform is constructed to acquire kinematics information. With the help of the sensor system, the coaches can combine attitude information with kinematics data to analyze the shot throwing movements.

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