• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.3
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• pp.577-592
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• 2023

In this study, nanofiber-based textile sensors were developed for motion detection and monitoring. Poly(vinylidene fluoride) (PVDF) nanofibers containing zinc oxide (ZnO) nanoparticles and silver nanowires (AgNW) were fabricated using electrospinning. PVDF was chosen as a piezoelectric polymer, zinc oxide as a piezoelectric ceramic, and AgNW as a metal to improve electric conductivity. The PVDF/ZnO/AgNW nanocomposite fibers were used to develop a textile sensor, which was then incorporated into an elbow band to develop a wearable smart band. Changes in the output voltage and peak-to-peak voltage (V_p-p) generated by the joint's flexion and extension were investigated using a dummy elbow. The β-phase crystallinity of pure PVDF nanofibers was 58% when analyzed using Fourier transform infrared spectroscopy; however, the β-phase crystallinity increased to 70% in PVDF nanofibers containing ZnO and to 78% in PVDF nanocomposite fibers containing both ZnO and AgNW. The textile sensor's output voltage values varied with joint-bending angle; upon increasing the joint angle from 45° to 90° to 150°, the V_p-p value increased from 0.321 V_p-p to 0.542 V_p-p to 0.660 V_p-p respectively. This suggests that the textile sensor can be used to detect and monitor body movements.

• Journal of Sensor Science and Technology
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• v.14 no.3
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• pp.156-159
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• 2005

Liposomes are microscopic spherical vesicles that form when lipids are hydrated and have been widely used for biochemical assay, drug delivery and molecular imaging. In particular, they are well known for artificial cell membranes to study cellular functions such as cell fusions and membrane proteins. Here, we firstly report the detection of liposomes by the highly sensitive microfabricated piezoresistive cantilever sensor chip and the phosphatidylserine recognition protein C2A which is chemically immobilized on the sensor surface. The signal created from the bending motion of piezoresistive cantilever after the liposome attachment has been monitored in real time.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.9
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• pp.957-963
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• 2014

This paper proposes a predictive control for an efficient human following robot using Kinect sensor. Especially, this research is focused on detecting of foot-end-point and foot-vector instead of human body which can be occluded easily by the obstacles. Recognition of the foot-end-point by the Kinect sensor is reliable since the two feet images can be utilized, which increases the detection possibility of the human motion. Depth image features and a decision tree have been utilized to estimate the foot end-point precisely. A tracking point average algorithm is also adopted in this research to estimate the location of foot accurately. Using the continuous locations of foot, the human motion trajectory is estimated to guide the mobile robot along a smooth path to the human. It is verified through the experiments that detecting foot-end-point is more reliable and efficient than detecting the human body. Finally, the tracking performance of the mobile robot is demonstrated with a human motion along an 'L' shape course.

• Smart Media Journal
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• v.5 no.3
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• pp.25-29
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• 2016

This paper presents research for non-contact gesture recognition system using EPS(Electronic Potential Sensor) for measuring the human body of electromagnetic fields. It implemented a signal acquisition and signal processing system for designing a system suitable for motion recognition using the data coming from the sensors. we transform AC-type data into DC-type data by applying a 10Hz LPF considering H/W sampling rate. in addition, we extract 2-dimensional movement information by taking difference value between two cross-diagonal deployed sensor.

• Korean Journal of Applied Biomechanics
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• v.21 no.4
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• pp.495-501
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• 2011

The purpose of this study was to develop the inertial sensor module system to detect gait event using single angular rate sensor(gyroscope), and evaluate the accuracy of this system. This sensor module is attached at the heel and gait events such as heel strike, foot flat, heel off, toe off are detected by using proposed automatic event detection algorithm. The developed algorithm detect characteristics of pitch data of the gyroscope to find gait event. To evaluate the accuracy of system, 3D motion capture system was used and synchronized with sensor module system for comparison of gait event timings. In experiment, 6 subjects performed 5 trials level walking with 3 different conditions such as slow, preferred and fast. Results showed that gait event timings by sensor module system are similar to that by kinematic data, because maximum absolute errors were under 37.4msec regardless of gait velocity. Therefore, this system can be used to detect gait events. Although this system has advantages of small, light weight, long-term monitoring and high accuracy, it is necessary to improve the system to get other gait information such as gait velocity, stride length, step width and joint angles.

• Journal of Sensor Science and Technology
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• v.20 no.6
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• pp.375-381
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• 2011

Ionic polymer-metal composite(IPMC) consists of an ion conductive membrane plated by metallic electrodes on both surfaces. When it bends, a voltage is generated between two electrodes. Since IPMC is flexible and thin, it can be easily mounted on the various surfaces of a body. The present study investigates a sensor system using IPMC to effectively detect the bending angles applied on IPMC sensor. The paper evaluates several R and C circuit models that describe the physical composition of IPMC and selects the best model for the detection of angles. The circuit models implemented with a charge model describe the relationship between input bending angles and output voltages. The identification of R and C values was performed by minimizing the error between the real output voltages and the simulated output voltages from the circuit models of IPMC sensor. Then the output signal of a sensor was fed into the inverse model of the identified model to reproduce the bending angles. In order to support the validation of the model, the output voltages from an arbitrary bending motion were also applied to the selected inverse model, which successfully reproduced the arbitrary bending motion.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.361-367
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• 2010

This paper reports the development of a mobile robot for patrol using a single laser range finder. A Laser range finder is useful for outdoor environment regardless of illumination change or various weather conditions. In this paper we combined the motion control of the mobile robot and the algorithm for detecting the outdoor environment. For obstacle avoidance, we adopted the Vector Field Histogram algorithm. A laser range finder is mounted on the mobile robot and looking down the road with a small tilt angle. We propose an algorithm for detecting the surface of the road. The outdoor patrol robot platform is equipped with a DGPS system, a gyro-compass sensor, and a laser range finder. The proposed obstacle avoidance and road detection algorithms were experimentally tested in success.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.321-323
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• 2015

Monitoring crane motion in real time is the first step to identifying and mitigating crane-related hazards on construction sites. However, no accurate and reliable crane motion capturing technique is available to serve this purpose. The objective of this research is to explore a method for real-time crane motion capturing and investigate an approach for assisting hazard detection. To achieve this goal, this research employed various techniques including: 1) a sensor-based method that accurately, reliably, and comprehensively captures crane motions in real-time; 2) computationally efficient algorithms for fusing and processing sensing data (e.g., distance, angle, acceleration) from different types of sensors; 3) an approach that integrates crane motion data with known as-is environment data to detect hazards associated with lifting tasks; and 4) a strategy that effectively presents crane operator with crane motion information and warn them with potential hazards. A prototype system was developed and tested on a real crane in a field environment. The results show that the system is able to continuously and accurately monitor crane motion in real-time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2427-2432
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• 2009

This paper proposes an monitoring system of elder and feeble person's motion activity using an object's motion activity data. The proposed system used wireless 3-axis sensor module, product by Freescale(Wireless Sensing Triple Axis Reference Design Board (ZSTAR)). We distribute sensing data into three classes using Neural Network System SVM. We find performance of proposed system that simulate some case about walk, past walk, fallen. Classify result data and graph of sensing data present succes rate 80%.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.363-365
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• 2007

Novel concept of sensor mat and its signal processing method is proposed for patient monitoring in medical application. Proposed sensor mat structure has sensing inner layer which has cross-linked arrangement using plastic optical fiber(POF). Large core diameter of plastic optical fiber behaved as band pass filter by averaging the noise component. caused by unwanted environmental factors. Signal processor followed by sensor output added noise immune performance by filtering out unwanted component. Fail-proof patient breath monitoring scheme was realized by using intelligent decision algorithm. Unlike the conventional approach by using mechanical sensor, which have high sensitivity both to intruder and to environmental noise, our approach provided reliable breath motion detection.