Development of a low power motion tracking wireless node for IoT applications

Motion tracking technology offers the ability to detect and record movements of an object or human. This technology has been widely used in many fields such as gaming industry, sports and biomedical. Motion tracking typically uses sensors such as accelerometer, gyroscope and magnetometer to measure...

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Main Author: Christina, Grace
Other Authors: Vun Chan Hua, Nicholas
Format: Final Year Project
Language:English
Published: 2017
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Online Access:http://hdl.handle.net/10356/70349
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-703492023-03-03T20:35:46Z Development of a low power motion tracking wireless node for IoT applications Christina, Grace Vun Chan Hua, Nicholas School of Computer Science and Engineering DRNTU::Engineering::Computer science and engineering Motion tracking technology offers the ability to detect and record movements of an object or human. This technology has been widely used in many fields such as gaming industry, sports and biomedical. Motion tracking typically uses sensors such as accelerometer, gyroscope and magnetometer to measure movements of humans’ joints. This project aims to develop motion tracking node using Inertial Measurement Unit (IMU) interfaced with low power microcontroller. IMU is a device that measures the change in orientation, angular rate and magnetic field surrounding the moving body. Multiples of this tracking node can be attached to human body parts, such as knees, hips or ankles. These tracking nodes then regularly send sensors’ movement data to a central device, which in this case is a Raspberry Pi for further processing. Fusion of data from multiple tracking nodes can hence be used to track the joint orientation of body parts that they are attached to, such as knees, hips or ankles. All the data processing are performed in the Raspberry Pi. Drifts and offset will appear during the sensors’ data transfer from multiple motion tracking nodes to the central device. As a result, the joint orientation will not be accurate due to these offsets. As such, time synchronization between the devices is implemented to enable monitoring the drift. Bachelor of Engineering (Computer Engineering) 2017-04-21T01:04:40Z 2017-04-21T01:04:40Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/70349 en Nanyang Technological University 56 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Christina, Grace
Development of a low power motion tracking wireless node for IoT applications
description Motion tracking technology offers the ability to detect and record movements of an object or human. This technology has been widely used in many fields such as gaming industry, sports and biomedical. Motion tracking typically uses sensors such as accelerometer, gyroscope and magnetometer to measure movements of humans’ joints. This project aims to develop motion tracking node using Inertial Measurement Unit (IMU) interfaced with low power microcontroller. IMU is a device that measures the change in orientation, angular rate and magnetic field surrounding the moving body. Multiples of this tracking node can be attached to human body parts, such as knees, hips or ankles. These tracking nodes then regularly send sensors’ movement data to a central device, which in this case is a Raspberry Pi for further processing. Fusion of data from multiple tracking nodes can hence be used to track the joint orientation of body parts that they are attached to, such as knees, hips or ankles. All the data processing are performed in the Raspberry Pi. Drifts and offset will appear during the sensors’ data transfer from multiple motion tracking nodes to the central device. As a result, the joint orientation will not be accurate due to these offsets. As such, time synchronization between the devices is implemented to enable monitoring the drift.
author2 Vun Chan Hua, Nicholas
author_facet Vun Chan Hua, Nicholas
Christina, Grace
format Final Year Project
author Christina, Grace
author_sort Christina, Grace
title Development of a low power motion tracking wireless node for IoT applications
title_short Development of a low power motion tracking wireless node for IoT applications
title_full Development of a low power motion tracking wireless node for IoT applications
title_fullStr Development of a low power motion tracking wireless node for IoT applications
title_full_unstemmed Development of a low power motion tracking wireless node for IoT applications
title_sort development of a low power motion tracking wireless node for iot applications
publishDate 2017
url http://hdl.handle.net/10356/70349
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