• Title/Summary/Keyword: Motion Sensors

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Recent Trends in Human Motion Detection Technology and Flexible/stretchable Physical Sensors: A Review

  • Park, Inkyu
    • Journal of Sensor Science and Technology
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    • v.26 no.6
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    • pp.391-396
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    • 2017
  • Human body motion detection is important in several industry sectors, such as entertainment, healthcare, rehabilitation, and so on. In this paper, we first discuss commercial human motion detection technologies (optical markers, MEMS acceleration sensors, infrared imaging, etc.) and then explain recent advances in the development of flexible and stretchable strain sensors for human motion detection. In particular, flexible and stretchable strain sensors that are fabricated using carbon nanotubes, silver nanowires, graphene, and other materials are reviewed.

Development of Real-Data Motion Sensor Emulator (실측 데이터 기반 모션센서 에뮬레이터의 개발)

  • Lee, MinSuk
    • IEMEK Journal of Embedded Systems and Applications
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    • v.6 no.2
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    • pp.68-75
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    • 2011
  • This paper describes the development of an open source motion sensor emulator. It helps developers to understand the motion sensor and its data better. Through this emulator, the realtime or stored motion sensor data can be applied to the applications that utilize motion sensors. The data of motion sensors which include accelerometer sensor, magnetic field sensor, gyro sensor, GPS, and so on, can be collected by using smart phones or motion sensors. We also describe a visualizer which shows various graphs, video and 3D animations based on the data sent by the emulator. It helps developers to understand motion sensors and how to use the sensors. The developed emulator is compatible with Android sensor simulator.

Comparison of Motion Sensor Systems for Gait Phase Detection (보행주기 검출용 모션 센서 시스템의 비교)

  • Park, Sun-Woo;Sohn, Ryang-Hee;Ryu, Ki-Hong;Kim, Young-Ho
    • Journal of the Korean Society for Precision Engineering
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    • v.27 no.2
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    • pp.145-152
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    • 2010
  • Gait phase detection is important for evaluating the recovery of gait ability in patients with paralysis, and for determining the stimulation timing in FES walking. In this study, three different motion sensors(tilt sensor, gyrosensor and accelerometer) were used to detect gait events(heel strike, HS; toe off, TO) and they were compared one another to determine the most applicable sensor for gait phase detection. Motion sensors were attached on the shank and heel of subjects. Gait phases determined by the characteristics of each sensor's signal were compared with those from FVA. Gait phase detections using three different motion sensors were valid, since they all have reliabilities more than 95%, when compared with FVA. HS and TO were determined by both FVA and motion sensor signals, and the accuracy of detecting HS and TO with motion sensors were assessed by the time differences between FVA and motion sensors. Results show of that the tilt sensor and the gyrosensor could detect gait phase more accurately in normal subjects. Vertical acceleration from the accelerometer could detect HS most accurately in hemiplegic patient group A. The gyrosensor could detect HS and TO most accurately in hemiplegic patient group A and B. Valid error ranges of HS and TO were determined by 3.9 % and 13.6 % in normal subjects, respectively. The detection of TO from all sensor signals was valid in both patient group A and B. However, the vertical acceleration detected HS validly in patient group A and the gyrosensor detected HS validly in patient group B. We could determine the most applicable motion sensors to detect gait phases in hemiplegic patients. However, since hemiplegic patients have much different gait patterns one another, further experimental studies using various simple motion sensors would be required to determine gait events in pathologic gaits.

The Optimization of the Number and Positions of Foot Pressure Sensors to Develop Smart Shoes

  • Yoo, Sihyun;Gil, Hojong;Kim, Jongbin;Ryu, Jiseon;Yoon, Sukhoon;Park, Sang Kyoon
    • Journal of the Ergonomics Society of Korea
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    • v.36 no.5
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    • pp.395-409
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    • 2017
  • Objective: The purpose of this study was to optimize the number and positions of foot pressure sensors using the reliability analysis of the center of pressure (COP) in smart shoes. Background: Foot pressure can be different according to foot region, and it is important which region of the foot pressure needs to be measured. Method: Thirty adults (age: $20.5{\pm}1.8years$, body weight: $71.4{\pm}6.5kg$, height: $1.76{\pm}0.04m$) participated in this study. The foot pressure data were collected using the insole of Pedar-X system (Novel GmbH, USA) with a sampling frequency of 100Hz during 1.3m/s speed walking on the treadmill (Instrumented treadmill, Bertec, USA). The intraclass correlation coefficients (ICC) were calculated between the COP positions using 4, 5, 6, 7, 8, and 99 sensors, while one-way repeated measure ANOVA was performed between the standard deviation (SD) of the COP positions. Results: The medio-lateral (M/L) COP position using 99 sensors was positively correlated with the M/L COP positions using 6, 7, and 8 sensors; however, it was not correlated with the M/L COP positions using 4 and 5 sensors during landing phase (1~4%) (p<.05). The antero-posterior (A/P) COP position using 99 sensors was positively correlated with the A/P COP positions using 4, 5, 6, 7, and 8 sensors (p<.05). The SD of the COP position using 99 sensors was smaller than the SD of the M/L COP positions using 4, 5, 6, 7, and 8 sensors (p<.05). Conclusion: Based on our findings, it is desirable to arrange at least 6 sensors in smart shoes. Application: The study of optimizing the number and positions of foot pressure sensors would contribute to developing more effective smart shoes using foot pressure technology.

Motion Capture of the Human Body Using Multiple Depth Sensors

  • Kim, Yejin;Baek, Seongmin;Bae, Byung-Chull
    • ETRI Journal
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    • v.39 no.2
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    • pp.181-190
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    • 2017
  • The movements of the human body are difficult to capture owing to the complexity of the three-dimensional skeleton model and occlusion problems. In this paper, we propose a motion capture system that tracks dynamic human motions in real time. Without using external markers, the proposed system adopts multiple depth sensors (Microsoft Kinect) to overcome the occlusion and body rotation problems. To combine the joint data retrieved from the multiple sensors, our calibration process samples a point cloud from depth images and unifies the coordinate systems in point clouds into a single coordinate system via the iterative closest point method. Using noisy skeletal data from sensors, a posture reconstruction method is introduced to estimate the optimal joint positions for consistent motion generation. Based on the high tracking accuracy of the proposed system, we demonstrate that our system is applicable to various motion-based training programs in dance and Taekwondo.

Triboelectric Nanogenerators for Self-powered Sensors

  • Rubab, Najaf;Kim, Sang-Woo
    • Journal of Sensor Science and Technology
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    • v.31 no.2
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    • pp.79-84
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    • 2022
  • Self-powered sensors play an important role in everyday life, and they cover a wide range of topics. These sensors are meant to measure the amount of relevant motion and transform the biomechanical activities into electrical signals using triboelectric nanogenerators (TENGs) since they are sensitive to external stimuli such as pressure, temperature, wetness, and motion. The present advancement of TENGs-based self-powered wearable, implantable, and patchable sensors for healthcare monitoring, human body motion, and medication delivery systems was carefully emphasized in this study. The use of TENG technology to generate electrical energy in real-time using self-powered sensors has been the topic of considerable research among various leading scholars. TENGs have been used in a variety of applications, including biomedical and healthcare physical sensors, wearable devices, biomedical, human-machine interface, chemical and environmental monitoring, smart traffic, smart cities, robotics, and fiber and fabric sensors, among others, as efficient mechanical-to-electric energy conversion technologies. In this evaluation, the progress accomplished by TENG in several areas is extensively reviewed. There will be a discussion on the future of self-powered sensors.

Development of Motion Reference Unit for Autonomous Underwater Vehicle (자율무인잠수정의 자세계측장치의 개발)

  • 김도현;오준호
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.1
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    • pp.101-108
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    • 1998
  • This paper concerns the navigation algorithm of motion reference unit (MRU) for autonomous underwater vehicle (AUV) We apply the strapdown navigation system using middle level inertial sensors. But, because the MRU consists of inertial sensors, the values of AUV motion calculated by navigation computer are increased by drift property of inertial sensors. Therefore, we propose the attitude algorithm using switching method according to the motion of AUV From this algorithm, the drift terms are eliminated effectively for roll and pitch. But, another device is required for yaw angle.

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Motion Capture System using Integrated Pose Sensors (융합센서 기반의 모션캡처 시스템)

  • Kim, Byung-Yul;Han, Young-Joon;Hahn, Hern-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.4
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    • pp.65-74
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    • 2010
  • At the aim of solving the problems appearing in traditional optical motion capturing systems such as the interference among multiple patches and the complexity of sensor and patch allocations, this paper proposes a new motion capturing system which is composed of a single camera and multiple motion sensors. A motion sensor is consisted of an acceleration sensor and a gyro sensor to detect the motion of a patched body and the orientation (roll, pitch, and yaw) of the motion, respectively. Although Image information provides the positions of the patches in 2D, the orientation information of the patch motions acquired by the motion sensors can generate 3D pose of the patches using simple equations. Since the proposed system uses the minimum number of sensors to detect the relative pose of a patch, it is easy to install on a moving body and can be economically used for various applications. The performance and the advantages of the proposed system have been proved by the experiments.

Evaluating Joint Motion Sensing Efficiency According to the Implementation Method of CNT-Based Fabric Sensors (CNT 기반의 직물센서 구현 방법에 따른 관절동작 센싱 효율 평가)

  • Cho, Hyun-Seung;Yang, Jin-Hee;Lee, Joo-Hyeon
    • Science of Emotion and Sensibility
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    • v.24 no.4
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    • pp.129-138
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    • 2021
  • This study aimed to determine the effects of the shape and attachment position of stretchable textile sensors coated with carbon nanotube on their performance when used to measure children's joint movements. Moreover, the child-safe requirements for fabric motion sensors are established. The child participants were advised to wear integrated clothing equipped with the sensors of various shapes (rectangular and boat-shaped) and attachment positions (at the knee and elbow joints or 4 cm below the joints). The voltage change induced by the elongation and contraction of the fabric sensors was determined for arm and leg flexion-extension motions at 60 deg/s (three measurements of 10 repeats each for 60°and 90°angles, for a total of 60 repetitions). Their dependability was determined by comparing the fabric motion sensors to the associated acceleration sensors. The experimental results indicate that the rectangular-shaped sensor affixed 4 cm below the joint is the most effective fabric motion sensor for measuring children's arm and leg motions. In this study, we designed a textile sensor capable of tracking children's joint motion and analyzed the sensor shape and attachment position on motion sensing clothing. We demonstrated that flexible fabric sensors integrated into garments may be used to detect the joint motions of the human body.

Implementation of Rule-based Smartphone Motion Detection Systems

  • Lee, Eon-Ju;Ryou, Seung-Hui;Lee, So-Yun;Jeon, Sung-Yoon;Park, Eun-Hwa;Hwang, Jung-Ha;Choi, Doo-Hyun
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.7
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    • pp.45-55
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    • 2021
  • Information obtained through various sensors embedded in a smartphone can be used to identify and analyze user's movements and situations. In this paper, we propose two rule-based motion detection systems that can detect three alphabet motions, 'I', 'S', and 'Z' by analyzing data obtained by the acceleration and gyroscope sensors in a smartphone. First of all, the characteristics of acceleration and angular velocity for each motion are analyzed. Based on the analysis, two rule-based systems are proposed and implemented as an android application and it is used to verify the detection performance for each motion. Two rule-based systems show high recognition rate over 90% for each motion and the rule-based system using ensemble shows better performance than another one.